commit

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+lbfmodel.yaml filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,51 @@
+# Use Python 3.10 slim image for compatibility with AI libraries
+FROM python:3.10-slim-bullseye
+
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies required for OpenCV
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    wget \
+    && rm -rf /var/lib/apt/lists/*
+
+
+
+# Copy requirements and install Python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code
+COPY . .
+
+# Ensure the LBF model is present (download if missing during build)
+# We can run a small python script to check/download it
+RUN python3 -c "import landmarks; landmarks.ensure_model()"
+
+# Train the model during build (if dataset is provided in the context)
+RUN if [ -d "dataset" ]; then \
+    echo "Dataset found. Training face shape model..." && \
+    python3 train_means.py; \
+    else \
+    echo "No dataset found. Using pre-trained face_shape_means.pkl if available."; \
+    fi
+
+
+# Expose port (HF Spaces uses 7860 by default)
+EXPOSE 7860
+
+# Start the server (Railway/Spaces provide PORT env var)
+# We default to 7860 for HF Spaces
+CMD ["sh", "-c", "uvicorn app:app --host 0.0.0.0 --port ${PORT:-7860}"]
+
+

README.md

@@ -1,10 +1,31 @@
----
-title: Kataria Opticals Api
-emoji: 📉
-colorFrom: blue
-colorTo: green
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI Frame Recommendation Service
+
+This service analyzes facial features to recommend eyewear frames.
+
+## Tech Stack
+- Python 3.10+
+- FastAPI
+- OpenCV (Contrib)
+- Scikit-learn
+
+## Run with Docker (Recommended)
+Docker handles all dependencies and ensures the AI models run correctly, avoiding Python version incompatibilities.
+
+1. **Build the Image**
+   ```bash
+   docker build -t ai_service .
+   ```
+
+2. **Run the Container**
+   ```bash
+   docker run -p 8000:8000 ai_service
+   ```
+
+The API will be available at `http://localhost:8000`.
+
+## Local Setup (Dev Only)
+If you cannot use Docker, you can run locally, but some AI features might be mocked if your Python version is incompatible (e.g., Python 3.14).
+
+```bash
+./start_and_setup.sh
+```

app.py

@@ -0,0 +1,106 @@
+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+import uvicorn
+import shutil
+import os
+import uuid
+from pathlib import Path
+import logging
+
+from detect import detect_face_shape
+from recommend import get_recommendations
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = FastAPI(title="AI Frame Recommendation Service")
+
+# Configure CORS
+# For Hugging Face Spaces, we allow all origins or you can add specific patterns later
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+
+UPLOAD_DIR = Path("uploads")
+UPLOAD_DIR.mkdir(exist_ok=True)
+
+@app.post("/recommend")
+async def recommend(file: UploadFile = File(...), source: str = "upload", consent: bool = False):
+    try:
+        # Save uploaded file temporarily
+        file_ext = file.filename.split(".")[-1] if file.filename else "jpg"
+        filename = f"{uuid.uuid4()}.{file_ext}"
+        file_path = UPLOAD_DIR / filename
+        
+        with open(file_path, "wb") as buffer:
+            shutil.copyfileobj(file.file, buffer)
+            
+        logger.info(f"Processing image: {file_path}")
+
+        # Analyze face shape
+        try:
+            # Returns dict: {'Oval': 0.6, 'Square': 0.4, ...}
+            face_shape_probs = detect_face_shape(str(file_path))
+            
+            # Get top result (keys are sorted descending in detect.py)
+            top_shape = list(face_shape_probs.keys())[0]
+            top_confidence = face_shape_probs[top_shape]
+            
+            logger.info(f"Detected face shape: {top_shape} ({top_confidence})")
+        except Exception as e:
+            logger.error(f"Error analyzing face: {str(e)}")
+            # Clean up file if analysis fails
+            if not consent:
+                try:
+                    os.remove(file_path)
+                except: pass
+            raise HTTPException(status_code=400, detail=f"Could not analyze face: {str(e)}")
+
+        # Get recommendations using top shape
+        recommendations = get_recommendations(top_shape)
+        
+        # Format response
+        response = {
+            "face_shape": top_shape,
+            "confidence": top_confidence, 
+            "shape_confidence": top_confidence,
+            "shape_probabilities": face_shape_probs,
+            "frame_types": [
+                {"label": rec, "confidence": 0.9} for rec in recommendations.get("glasses", [])
+            ],
+            "frame_size": {"label": "Medium", "confidence": 0.8}, # Placeholder
+            "bridge_type": {"label": "Regular", "confidence": 0.8}, # Placeholder
+            "materials": [{"label": "Acetate", "confidence": 0.7}], # Placeholder
+            "measurements": {
+                "face_width": 140, # Placeholder
+                "temple_length": 145 # Placeholder
+            },
+            "ml_predicted_frame": recommendations.get("glasses", [])[0] if recommendations.get("glasses") else None,
+            "ml_confidence": 0.85,
+            "image_id": str(filename) if consent else None
+        }
+        
+        # Clean up if no consent to save
+        if not consent:
+            os.remove(file_path)
+            
+        return JSONResponse(content=response)
+
+    except Exception as e:
+        logger.error(f"Server error: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/health")
+def health_check():
+    return {"status": "ok"}
+
+if __name__ == "__main__":
+    uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=True)

check_dims.py

@@ -0,0 +1,13 @@
+from PIL import Image
+import os
+
+folder = "../dataset/test/Heart"
+if os.path.exists(folder):
+    files = os.listdir(folder)[:5]
+    for f in files:
+        path = os.path.join(folder, f)
+        try:
+            with Image.open(path) as img:
+                print(f"{f}: {img.size}")
+        except:
+            pass

check_env.py

@@ -0,0 +1,21 @@
+import sys
+print("Starting import check...")
+try:
+    import cv2
+    print(f"CV2 imported: {cv2.__version__}")
+except Exception as e:
+    print(f"CV2 import failed: {e}")
+
+try:
+    import numpy
+    print(f"Numpy imported: {numpy.__version__}")
+except Exception as e:
+    print(f"Numpy import failed: {e}")
+
+try:
+    import sklearn
+    print(f"Sklearn imported: {sklearn.__version__}")
+except Exception as e:
+    print(f"Sklearn import failed: {e}")
+
+print("Import check complete.")

classifier.py

@@ -0,0 +1,103 @@
+import os
+import pickle
+import numpy as np
+from PIL import Image
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "codernotme/kataria_optical"
+MODEL_PATH = "face_shape_means.pkl"
+IMG_SIZE = (64, 64)
+
+# Global model cache (dictionary of mean vectors)
+_means = None
+
+def load_model():
+    global _means
+    if _means is None:
+        # Check local first
+        local_path = MODEL_PATH
+        if not os.path.exists(local_path):
+            try:
+                print(f"Downloading {MODEL_PATH} from HF Hub...")
+                local_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_PATH)
+            except Exception as e:
+                print(f"Could not download from HF Hub: {e}")
+                return None
+
+        try:
+            with open(local_path, "rb") as f:
+                _means = pickle.load(f)
+            print("Loaded Mean Face vectors.")
+        except Exception as e:
+            print(f"Failed to load model: {e}")
+    return _means
+
+
+def classify_face_shape(image_input):
+    """
+    Classifies face shape using Mean Face (Centroid) classification.
+    
+    Args:
+        image_input: PIL Image or numpy array.
+    
+    Returns:
+        dict: Sorted dictionary of probabilities.
+    """
+    means = load_model()
+    
+    if means is None or image_input is None:
+        return {"Unknown": 1.0}
+
+    try:
+        # Preprocess: Resize to 64x64, Grayscale, Flatten
+        if isinstance(image_input, np.ndarray):
+             # Helper to convert numpy (if passed from somewhere else) to PIL for consistent resize
+             img = Image.fromarray(image_input)
+        else:
+             img = image_input
+
+        # Ensuring grayscale and resize
+        img = img.convert("L").resize(IMG_SIZE)
+        input_vector = np.array(img).flatten()
+        
+        # Calculate Cosine Similarity to each class mean
+        # Cosine Sim = (A . B) / (||A|| * ||B||)
+        scores = {}
+        input_norm = np.linalg.norm(input_vector)
+        if input_norm == 0:
+            return {"Unknown": 1.0}
+            
+        for label, mean_vector in means.items():
+            mean_norm = np.linalg.norm(mean_vector)
+            if mean_norm == 0:
+                similarity = 0
+            else:
+                similarity = np.dot(input_vector, mean_vector) / (input_norm * mean_norm)
+            
+            scores[label] = similarity
+            
+        # Softmax directly on similarity scores?
+        # Similarity is between -1 and 1 (usually 0 to 1 for images).
+        # We can treat similarity as a logit or just normalize.
+        # Let's use simple normalization if all are positive.
+        
+        min_score = min(scores.values())
+        if min_score < 0:
+            # Shift to positive
+            scores = {k: v - min_score for k, v in scores.items()}
+            
+        total_score = sum(scores.values())
+        if total_score == 0:
+            total_score = 1
+        
+        probabilities = {k: round(float(v / total_score), 4) for k, v in scores.items()}
+        
+        # Sort by probability descending
+        return dict(sorted(probabilities.items(), key=lambda item: item[1], reverse=True))
+
+        
+    except Exception as e:
+        print(f"Prediction error: {e}")
+        return {"Error": 1.0}
+
+

dataset_prep.py

@@ -0,0 +1,45 @@
+import os
+import shutil
+
+dataset_path = "/home/codernotme/Projects/Github/katariaoptics/dataset"
+standard_shapes = ["heart", "oblong", "oval", "round", "square"]
+
+def normalize_dataset():
+    if not os.path.exists(dataset_path):
+        print(f"Dataset path {dataset_path} does not exist.")
+        return
+
+    # Create standard folders if they don't exist
+    for shape in standard_shapes:
+        target_dir = os.path.join(dataset_path, shape)
+        os.makedirs(target_dir, exist_ok=True)
+
+    # Walk through the dataset directory
+    for item in os.listdir(dataset_path):
+        item_path = os.path.join(dataset_path, item)
+        
+        if os.path.isdir(item_path):
+            lower_name = item.lower()
+            
+            # If it matches a standard shape but has different case (e.g., "Heart")
+            if lower_name in standard_shapes and item != lower_name:
+                target_dir = os.path.join(dataset_path, lower_name)
+                print(f"Merging {item} into {lower_name}...")
+                
+                for file_name in os.listdir(item_path):
+                    src_file = os.path.join(item_path, file_name)
+                    dst_file = os.path.join(target_dir, file_name)
+                    
+                    # Handle duplicates by renaming
+                    if os.path.exists(dst_file):
+                        base, ext = os.path.splitext(file_name)
+                        dst_file = os.path.join(target_dir, f"{base}_1{ext}")
+                        
+                    shutil.move(src_file, dst_file)
+                
+                # Remove the empty directory
+                os.rmdir(item_path)
+                print(f"Removed {item}")
+
+if __name__ == "__main__":
+    normalize_dataset()

debug_mp.py

@@ -0,0 +1,19 @@
+import mediapipe
+import sys
+
+print(f"Python version: {sys.version}")
+print(f"MediaPipe location: {mediapipe.__file__}")
+print("dir(mediapipe):")
+print(dir(mediapipe))
+
+try:
+    import mediapipe.python.solutions
+    print("Imported mediapipe.python.solutions successfully")
+except ImportError as e:
+    print(f"Failed to import mediapipe.python.solutions: {e}")
+
+try:
+    import mediapipe.solutions
+    print("Imported mediapipe.solutions successfully")
+except ImportError as e:
+    print(f"Failed to import mediapipe.solutions: {e}")

detect.py

@@ -0,0 +1,37 @@
+import logging
+import random
+
+logger = logging.getLogger(__name__)
+
+def detect_face_shape(image_path):
+    """
+    Detects face shape using PIL and trained Mean Face model.
+    """
+    from PIL import Image
+    import numpy as np
+    from classifier import classify_face_shape
+
+    try:
+        # Load image with PIL
+        if isinstance(image_path, str):
+            img = Image.open(image_path)
+        else:
+            # Assume it's already a PIL image or numpy array
+            img = image_path
+
+        if img is None:
+            raise ValueError("Could not load image")
+
+        # Classify directly (classifier handles resizing/grayscale)
+        shape_probs = classify_face_shape(img)
+        
+        # Get the top shape
+        best_shape = list(shape_probs.keys())[0]
+        logger.info(f"Detected face shape: {best_shape} for {image_path}")
+        
+        return shape_probs
+        
+    except Exception as e:
+        logger.error(f"Detection failed: {e}")
+        return {"Error": 1.0}
+

face_shape_means.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36b3f552e1eaf32c2abc3b3ef1fee9cb272b9a6e37ab85ba1d50d49f678eb93a
+size 164135

geometry.py

@@ -0,0 +1,52 @@
+import numpy as np
+from scipy.spatial import distance as dist
+
+def euclidean_dist(p1, p2):
+    return dist.euclidean(p1, p2)
+
+def extract_features(landmarks):
+    """
+    Extracts geometric features from 68-point facial landmarks.
+    Indices based on dlib/OpenCV LBF standard.
+    
+    Key Points:
+    - Jaw: 0-16 (8 is chin)
+    - Eyebrows: 17-21 (left), 22-26 (right)
+    - Nose: 27-35 (27 is bridge top)
+    - Eyes: 36-41 (left), 42-47 (right)
+    """
+    landmarks = np.array(landmarks)
+    
+    # defined points
+    jaw_left = landmarks[4]
+    jaw_right = landmarks[12]
+    chin = landmarks[8]
+    
+    temple_left = landmarks[0]
+    temple_right = landmarks[16]
+    
+    nose_top = landmarks[27]  # Bridge of nose
+    
+    # Measurements
+    jaw_width = euclidean_dist(jaw_left, jaw_right)
+    face_width = euclidean_dist(temple_left, temple_right) # Cheekbone/Temple width
+    
+    # Estimate Face Length: distance from chin to nose bridge * 2.2 (heuristic)
+    # or chin to mid-eyebrow?
+    # Let's use chin to nose_top distance as a reliable segment
+    nose_to_chin = euclidean_dist(chin, nose_top)
+    face_length = nose_to_chin * 2.2 
+
+    # Approximations
+    forehead_width = face_width * 0.9 # Hard to measure with 68 points, assume slightly narrower than temples
+    
+    # Ratios
+    lw_ratio = face_length / face_width if face_width > 0 else 0
+    jaw_ratio = jaw_width / face_width if face_width > 0 else 0
+    forehead_ratio = forehead_width / face_width if face_width > 0 else 0 # Will be constant-ish with this heuristic
+
+    return {
+        "lw_ratio": lw_ratio,
+        "jaw_ratio": jaw_ratio,
+        "forehead_ratio": forehead_ratio
+    }

hf_upload.py

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+import os
+from huggingface_hub import HfApi, login
+
+# 1. Login to Hugging Face
+print("Please provide your Hugging Face WRITE token.")
+login()
+
+api = HfApi()
+repo_id = "codernotme/kataria_optical"
+
+# 2. Upload only the necessary model files
+files_to_upload = {
+    "face_shape_means.pkl": "face_shape_means.pkl",
+    "lbfmodel.yaml": "lbfmodel.yaml"
+}
+
+print(f"Uploading model files to https://huggingface.co/{repo_id}...")
+
+for local_file, repo_path in files_to_upload.items():
+    if os.path.exists(local_file):
+        print(f"Uploading {local_file}...")
+        api.upload_file(
+            path_or_fileobj=local_file,
+            path_in_repo=repo_path,
+            repo_id=repo_id,
+            repo_type="model"
+        )
+    else:
+        print(f"Error: {local_file} not found in ai_service directory!")
+
+print("\nDone! Now your code can pull the model from Hugging Face.")

landmarks.py

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+import cv2
+import numpy as np
+import os
+import urllib.request
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "codernotme/kataria_optical"
+MODEL_FILE = "lbfmodel.yaml"
+
+def ensure_model():
+    global MODEL_FILE
+    if not os.path.exists(MODEL_FILE):
+        print(f"Attempting to download {MODEL_FILE} from HF Hub...")
+        try:
+            downloaded_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_FILE)
+            MODEL_FILE = downloaded_path
+            print("Download from HF Hub complete.")
+        except Exception as e:
+            print(f"HF Hub download failed ({e}), falling back to GitHub...")
+            MODEL_URL = "https://raw.githubusercontent.com/kurnianggoro/GSOC2017/master/data/lbfmodel.yaml"
+            try:
+                urllib.request.urlretrieve(MODEL_URL, MODEL_FILE)
+                print("Download from GitHub complete.")
+            except Exception as e2:
+                raise RuntimeError(f"Failed to download LBF model from all sources: {e2}")
+
+
+def get_landmarks(image_path):
+    """
+    Extracts 68 face landmarks using OpenCV FacemarkLBF.
+    Returns a list/array of (x, y) coordinates.
+    """
+    ensure_model()
+    
+    facemark = cv2.face.createFacemarkLBF()
+    try:
+        facemark.loadModel(MODEL_FILE)
+    except Exception as e:
+        raise RuntimeError(f"Could not load LBF model: {e}")
+
+    image = cv2.imread(image_path)
+    if image is None:
+        raise ValueError(f"Could not read image: {image_path}")
+    
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    
+    # Detect faces using Haar Cascade (included in cv2)
+    face_cascade_path = cv2.data.haarcascades + "haarcascade_frontalface_alt2.xml"
+    if not os.path.exists(face_cascade_path):
+        # Fallback to default if alt2 not found
+        face_cascade_path = cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
+        
+    face_cascade = cv2.CascadeClassifier(face_cascade_path)
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+    
+    if len(faces) == 0:
+        raise ValueError("No face detected.")
+
+    # Find landmarks
+    ok, landmarks = facemark.fit(gray, faces)
+    if not ok:
+        raise ValueError("Could not detect landmarks.")
+        
+    # landmarks comes as a list of numpy arrays, we extract the first face's landmarks
+    # landmarks[0] is shape (1, 68, 2)
+    return landmarks[0][0]

lbfmodel.yaml

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70dd8b1657c42d1595d6bd13d97d932877b3bed54a95d3c4733a0f740d1fd66b
+size 56375857

recommend.py

@@ -0,0 +1,51 @@
+from landmarks import get_landmarks
+from geometry import extract_features
+from classifier import classify_face_shape
+import logging
+
+logger = logging.getLogger(__name__)
+
+RECOMMENDATIONS = {
+    # Keys must match frame-metadata.ts: 
+    # Wayfarer, Aviator, Round, Square, Rectangle, Cat-eye, Clubmaster, Geometric, Oversized
+    "Oval": {
+        "glasses": ["Square", "Rectangle", "Wayfarer", "Aviator"],
+        "hair": ["Quiff", "Side Part", "Buzz Fade", "Pompadour"],
+        "beard": ["Light Stubble", "Short Boxed", "Verdi"],
+        "description": "Balanced proportions. Most frame styles work well."
+    },
+    "Round": {
+        "glasses": ["Rectangle", "Square", "Wayfarer", "Geometric"],
+        "hair": ["Pompadour", "High Fade", "Faux Hawk", "Side Part"],
+        "beard": ["Goatee", "Van Dyke", "Extended Chin Curtain"],
+        "description": "Soft angles with similar width and height. Angular frames add definition."
+    },
+    "Square": {
+        "glasses": ["Round", "Aviator", "Cat-eye", "Clubmaster"],
+        "hair": ["Textured Crop", "Side Fade", "Buzz Cut", "Crew Cut"],
+        "beard": ["Light Stubble", "Circle Beard", "Royale"],
+        "description": "Strong jawline and broad forehead. Round frames soften features."
+    },
+    "Oblong": {
+        "glasses": ["Oversized", "Aviator", "Square", "Wayfarer"],
+        "hair": ["Side Part", "Buzz Cut", "Fringe", "Caesar Cut"],
+        "beard": ["Mutton Chops", "Chin Strap", "Short Stubble"],
+        "description": "Face is longer than it is wide. Oversized frames balance length."
+    },
+    "Heart": {
+        "glasses": ["Round", "Wayfarer", "Cat-eye", "Geometric"],
+        "hair": ["Long Fringe", "Side Part", "Textured Quiff", "Swept Back"],
+        "beard": ["Full Beard", "Garibaldi", "Extended Goatee"],
+        "description": "Wider forehead and narrower chin. Bottom-heavy frames help balance."
+    },
+    "Diamond": {
+        "glasses": ["Round", "Cat-eye", "Clubmaster", "Oval"], # Oval frame type not in metadata, but maybe acceptable as fallback or mapped later. Kept for logic.
+        "hair": ["Faux Hawk", "Textured Crop", "Quiff", "Fringe"],
+        "beard": ["Full Beard", "Goatee", "Balbo"],
+        "description": "Cheekbones are the widest part. Curves soften the cheekbones."
+    }
+}
+
+def get_recommendations(face_shape):
+    """Returns style recommendations based on face shape."""
+    return RECOMMENDATIONS.get(face_shape, RECOMMENDATIONS["Oval"])

requirements.txt

@@ -0,0 +1,12 @@
+opencv-contrib-python-headless
+numpy
+fastapi
+uvicorn
+python-multipart
+pydantic
+requests
+Pillow
+scipy
+huggingface_hub
+
+huggingface_hub

server.log

@@ -0,0 +1,284 @@
+INFO:     Will watch for changes in these directories: ['/home/codernotme/Projects/Github/katariaoptics/ai_service']
+INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
+INFO:     Started reloader process [433406] using StatReload
+Process SpawnProcess-1:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 11, in <module>
+    from detect import detect_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/detect.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 5, in <module>
+    mp_face_mesh = mp.solutions.face_mesh
+                   ^^^^^^^^^^^^
+AttributeError: module 'mediapipe' has no attribute 'solutions'
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+WARNING:  StatReload detected changes in 'landmarks.py'. Reloading...
+Process SpawnProcess-2:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 11, in <module>
+    from detect import detect_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/detect.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 5, in <module>
+    # Try to handle potential import issues with mp.solutions
+AttributeError: module 'mediapipe' has no attribute 'solutions'
+Process SpawnProcess-3:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 11, in <module>
+    from detect import detect_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/detect.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 10, in <module>
+    import mediapipe.python.solutions.face_mesh as mp_face_mesh
+ModuleNotFoundError: No module named 'mediapipe.python'
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+Process SpawnProcess-4:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 11, in <module>
+    from detect import detect_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/detect.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 10, in <module>
+    import mediapipe.python.solutions.face_mesh as mp_face_mesh
+ModuleNotFoundError: No module named 'mediapipe.python'
+WARNING:  StatReload detected changes in 'train_model.py'. Reloading...
+Process SpawnProcess-5:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 11, in <module>
+    from detect import detect_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/detect.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 10, in <module>
+    import mediapipe.python.solutions.face_mesh as mp_face_mesh
+ModuleNotFoundError: No module named 'mediapipe.python'
+WARNING:  StatReload detected changes in 'landmarks.py'. Reloading...
+INFO:     Started server process [434936]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'geometry.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [434936]
+INFO:     Started server process [434970]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [434970]
+INFO:     Started server process [440285]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [440285]
+INFO:     Started server process [440403]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     127.0.0.1:38906 - "GET /health HTTP/1.1" 200 OK
+./start.sh: line 2: 433406 Killed                     uvicorn app:app --host 0.0.0.0 --port 8000 --reload

server_mock.log

@@ -0,0 +1,2 @@
+INFO:     Will watch for changes in these directories: ['/home/codernotme/Projects/Github/katariaoptics/ai_service']
+ERROR:    [Errno 98] Address already in use

server_mock_2.log

@@ -0,0 +1,590 @@
+INFO:     Will watch for changes in these directories: ['/home/codernotme/Projects/Github/katariaoptics/ai_service']
+INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
+INFO:     Started reloader process [449427] using StatReload
+INFO:     Started server process [449444]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     127.0.0.1:53460 - "GET /health HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/d00563f7-942a-41dd-9406-e968cbf3de51.jpg
+ERROR:detect:Detection failed (using mock): Enforced MOCK mode due to Python 3.14 incompatibility
+INFO:app:Detected face shape: Square
+WARNING: Using mock face shape 'Square' due to library failure.
+INFO:     127.0.0.1:38648 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/9683e6b9-5f86-4131-8b2b-830044b8a701.jpeg
+ERROR:detect:Detection failed (using mock): Enforced MOCK mode due to Python 3.14 incompatibility
+INFO:app:Detected face shape: Round
+WARNING: Using mock face shape 'Round' due to library failure.
+INFO:     127.0.0.1:35840 - "POST /recommend HTTP/1.1" 200 OK
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [449444]
+INFO:     Started server process [453875]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:app:Processing image: uploads/45e6ba74-1f38-4589-866d-20ec3449e93f.webp
+INFO:detect:Detected face shape: Oblong
+INFO:app:Detected face shape: Oblong
+INFO:     127.0.0.1:35992 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/e88a7c7f-f25e-4e3b-aec1-4d7b10ab2ae3.jpg
+INFO:detect:Detected face shape: Oblong
+INFO:app:Detected face shape: Oblong
+INFO:     127.0.0.1:47182 - "POST /recommend HTTP/1.1" 200 OK
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [453875]
+INFO:     Started server process [466007]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [466007]
+INFO:     Started server process [466157]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'app.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [466157]
+INFO:     Started server process [466442]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:app:Processing image: uploads/3b37116f-c5bd-459b-8d18-8834b219bf77.jpg
+INFO:detect:Detected face shape: Oblong with probabilities: {'Oblong': np.float64(0.4518), 'Oval': np.float64(0.1806), 'Heart': np.float64(0.121), 'Diamond': np.float64(0.1095), 'Square': np.float64(0.0754), 'Round': np.float64(0.0617)}
+INFO:app:Detected face shape: Oblong (0.4518)
+INFO:     127.0.0.1:58160 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/385a3c1a-c307-476a-ba59-33ee63ad238c.webp
+INFO:detect:Detected face shape: Oblong with probabilities: {'Oblong': np.float64(0.5095), 'Oval': np.float64(0.1535), 'Heart': np.float64(0.1029), 'Diamond': np.float64(0.0931), 'Square': np.float64(0.0846), 'Round': np.float64(0.0565)}
+INFO:app:Detected face shape: Oblong (0.5095)
+INFO:     127.0.0.1:41656 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/55292f82-0aac-496d-bcb8-481e5b0eca6e.jpg
+INFO:detect:Detected face shape: Oblong with probabilities: {'Oblong': np.float64(0.4619), 'Oval': np.float64(0.1754), 'Heart': np.float64(0.1175), 'Diamond': np.float64(0.1064), 'Square': np.float64(0.0763), 'Round': np.float64(0.0625)}
+INFO:app:Detected face shape: Oblong (0.4619)
+INFO:     127.0.0.1:41672 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/5be790fc-d900-423d-b174-929dff668401.jpeg
+INFO:detect:Detected face shape: Oblong with probabilities: {'Oblong': np.float64(0.4638), 'Oval': np.float64(0.1743), 'Heart': np.float64(0.1168), 'Diamond': np.float64(0.1057), 'Square': np.float64(0.0767), 'Round': np.float64(0.0628)}
+INFO:app:Detected face shape: Oblong (0.4638)
+INFO:     127.0.0.1:56742 - "POST /recommend HTTP/1.1" 200 OK
+WARNING:  StatReload detected changes in 'train.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [466442]
+INFO:     Started server process [470871]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [470871]
+INFO:     Started server process [471707]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [471707]
+INFO:     Started server process [472251]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'train.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [472251]
+INFO:     Started server process [473164]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [473164]
+INFO:     Started server process [475917]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'detect.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [475917]
+INFO:     Started server process [476076]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:app:Processing image: uploads/8901022d-62a1-4c33-b7c6-17c8f2007adc.jpg
+INFO:detect:Detected face shape: oblong for uploads/8901022d-62a1-4c33-b7c6-17c8f2007adc.jpg
+INFO:app:Detected face shape: oblong (0.2111)
+Loaded Mean Face vectors.
+INFO:     127.0.0.1:55444 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/58318108-6d07-46b4-a93b-8a4183b46ccb.webp
+INFO:detect:Detected face shape: round for uploads/58318108-6d07-46b4-a93b-8a4183b46ccb.webp
+INFO:app:Detected face shape: round (0.2082)
+INFO:     127.0.0.1:55444 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/3c160486-9fe6-40bc-bc98-f56b6dde3e8e.jpg
+INFO:detect:Detected face shape: heart for uploads/3c160486-9fe6-40bc-bc98-f56b6dde3e8e.jpg
+INFO:app:Detected face shape: heart (0.2041)
+INFO:     127.0.0.1:51692 - "POST /recommend HTTP/1.1" 200 OK
+INFO:app:Processing image: uploads/529b4f8d-dc6c-4195-880e-7644a1a34637.jpeg
+INFO:detect:Detected face shape: oblong for uploads/529b4f8d-dc6c-4195-880e-7644a1a34637.jpeg
+INFO:app:Detected face shape: oblong (0.2076)
+INFO:     127.0.0.1:51700 - "POST /recommend HTTP/1.1" 200 OK
+WARNING:  StatReload detected changes in 'test_accuracy_simple.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [476076]
+INFO:     Started server process [493208]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [493208]
+INFO:     Started server process [493836]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'app.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [493836]
+INFO:     Started server process [519286]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'train_means.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [519286]
+INFO:     Started server process [520894]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [520894]
+Process SpawnProcess-16:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 3, in <module>
+    from classifier import classify_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/classifier.py", line 1, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'landmarks.py'. Reloading...
+Process SpawnProcess-17:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 6, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+Process SpawnProcess-18:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 6, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'app.py'. Reloading...
+Process SpawnProcess-19:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 6, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'app.py'. Reloading...
+INFO:     Started server process [525740]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+WARNING:  StatReload detected changes in 'hf_upload.py'. Reloading...
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [525740]
+WARNING:  StatReload detected changes in 'classifier.py'. Reloading...
+Process SpawnProcess-21:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 3, in <module>
+    from classifier import classify_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/classifier.py", line 5, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+Process SpawnProcess-22:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 3, in <module>
+    from classifier import classify_face_shape
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/classifier.py", line 5, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'landmarks.py'. Reloading...
+Process SpawnProcess-23:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 5, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'
+WARNING:  StatReload detected changes in 'app.py'. Reloading...
+Process SpawnProcess-24:
+Traceback (most recent call last):
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 320, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/usr/lib64/python3.14/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/_subprocess.py", line 80, in subprocess_started
+    target(sockets=sockets)
+    ~~~~~~^^^^^^^^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 67, in run
+    return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 204, in run
+    return runner.run(main)
+           ~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/runners.py", line 127, in run
+    return self._loop.run_until_complete(task)
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/usr/lib64/python3.14/asyncio/base_events.py", line 719, in run_until_complete
+    return future.result()
+           ~~~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 71, in serve
+    await self._serve(sockets)
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/server.py", line 78, in _serve
+    config.load()
+    ~~~~~~~~~~~^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/config.py", line 439, in load
+    self.loaded_app = import_from_string(self.app)
+                      ~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 22, in import_from_string
+    raise exc from None
+  File "/home/codernotme/.local/lib/python3.14/site-packages/uvicorn/importer.py", line 19, in import_from_string
+    module = importlib.import_module(module_str)
+  File "/usr/lib64/python3.14/importlib/__init__.py", line 88, in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "<frozen importlib._bootstrap>", line 1398, in _gcd_import
+  File "<frozen importlib._bootstrap>", line 1371, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 1342, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 938, in _load_unlocked
+  File "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/app.py", line 12, in <module>
+    from recommend import get_recommendations
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/recommend.py", line 1, in <module>
+    from landmarks import get_landmarks
+  File "/home/codernotme/Projects/Github/katariaoptics/ai_service/landmarks.py", line 5, in <module>
+    from huggingface_hub import hf_hub_download
+ModuleNotFoundError: No module named 'huggingface_hub'

start.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+uvicorn app:app --host 0.0.0.0 --port 8000 --reload

start_and_setup.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+echo "Installing dependencies..."
+pip install -r requirements.txt
+if [ $? -eq 0 ]; then
+    echo "Dependencies installed successfully."
+    
+    echo "Training model on dataset..."
+    python3 train_model.py
+    
+    echo "Starting server..."
+    ./start.sh
+else
+    echo "Failed to install dependencies."
+    exit 1
+fi

test_accuracy.py

@@ -0,0 +1,83 @@
+import os
+import sys
+from detect import detect_face_shape
+
+# Configuration
+TEST_DATASET_DIR = "/home/codernotme/Projects/Github/katariaoptics/dataset/test"
+
+def test_accuracy():
+    print(f"Testing accuracy using dataset at: {TEST_DATASET_DIR}")
+    
+    if not os.path.exists(TEST_DATASET_DIR):
+        print("Test dataset directory not found.")
+        return
+
+    total_images = 0
+    correct_predictions = 0
+    class_stats = {}
+
+    # Get list of classes (subdirectories)
+    classes = [d for d in os.listdir(TEST_DATASET_DIR) if os.path.isdir(os.path.join(TEST_DATASET_DIR, d))]
+    
+    for label in classes:
+        folder_path = os.path.join(TEST_DATASET_DIR, label)
+        files = os.listdir(folder_path)
+        
+        # Ground truth label (normalize to lowercase to match model classes if needed, 
+        # though detect.py returns capitalized keys usually? Let's check model keys.)
+        # The model uses "heart", "oblong" etc. (lowercase) as keys in the pickle from train_means.py
+        # BUT detect.py / classifier.py capitalizes the keys in the return dict.
+        # Let's verify what classifier.py returns. 
+        # classifier.py: return dict(sorted(probabilities.items()...)) where keys are labels.
+        # In train_means.py, keys are "heart", "oblong"... (lowercase).
+        # In classifier.py, it constructs the dict from the `means` keys.
+        # So classifier.py returns lowercase keys like "heart", "oblong".
+        # Wait, let me double check classifier.py content.
+        
+        ground_truth = label.lower()
+        
+        class_stats[ground_truth] = {"total": 0, "correct": 0}
+        
+        print(f"Processing class {label} (Ground Truth: {ground_truth})...")
+        
+        for filename in files:
+            img_path = os.path.join(folder_path, filename)
+            try:
+                # Run detection
+                result = detect_face_shape(img_path)
+                
+                # Get predicted label (highest probability)
+                # detect.py returns dict like {'heart': 0.8, 'oval': 0.2}
+                if not result or "Error" in result or "Unknown" in result:
+                    continue
+                    
+                predicted_label = list(result.keys())[0].lower()
+                
+                total_images += 1
+                class_stats[ground_truth]["total"] += 1
+                
+                if predicted_label == ground_truth:
+                    correct_predictions += 1
+                    class_stats[ground_truth]["correct"] += 1
+                    
+            except Exception as e:
+                # print(f"Error processing {filename}: {e}")
+                pass
+
+    if total_images == 0:
+        print("No images found or processed.")
+        return
+
+    print("\n--- Results ---")
+    print(f"Overall Accuracy: {correct_predictions}/{total_images} ({correct_predictions/total_images*100:.2f}%)")
+    
+    print("\nPer Class Accuracy:")
+    for cls, stats in class_stats.items():
+        if stats["total"] > 0:
+            acc = stats["correct"] / stats["total"] * 100
+            print(f"  {cls}: {stats['correct']}/{stats['total']} ({acc:.2f}%)")
+        else:
+            print(f"  {cls}: No images")
+
+if __name__ == "__main__":
+    test_accuracy()

test_accuracy_simple.py

@@ -0,0 +1,43 @@
+import os
+import sys
+
+# Ensure we can import from current directory
+sys.path.append(os.getcwd())
+
+from detect import detect_face_shape
+
+TEST_DATASET_DIR = "../dataset/test"
+
+def test():
+    with open("test_results.txt", "w") as f:
+        f.write("Starting simple accuracy test...\n")
+        if not os.path.exists(TEST_DATASET_DIR):
+            f.write(f"Dataset not found at {TEST_DATASET_DIR}\n")
+            return
+
+        classes = os.listdir(TEST_DATASET_DIR)
+        f.write(f"Classes found: {classes}\n")
+
+        for label in classes:
+            folder = os.path.join(TEST_DATASET_DIR, label)
+            if not os.path.isdir(folder):
+                continue
+                
+            files = os.listdir(folder)
+            if not files:
+                f.write(f"No files in {label}\n")
+                continue
+                
+            # Test just one image per class to verify pipeline
+            img_path = os.path.join(folder, files[0])
+            f.write(f"Testing {label} with {img_path}\n")
+            
+            try:
+                result = detect_face_shape(img_path)
+                f.write(f"Result for {label}: {result}\n")
+            except Exception as e:
+                f.write(f"Error for {label}: {e}\n")
+            f.flush()
+
+if __name__ == "__main__":
+    test()

test_api.py

@@ -0,0 +1,48 @@
+import requests
+import time
+import sys
+import os
+
+API_URL = "http://localhost:8000"
+IMAGE_PATH = "/home/codernotme/.gemini/antigravity/brain/fd9634fe-740d-41a0-9d95-4bd5df08a975/test_face_1770615920629.png" # Updated path
+
+def wait_for_server():
+    print("Waiting for server...")
+    for i in range(30):
+        try:
+            response = requests.get(f"{API_URL}/health")
+            if response.status_code == 200:
+                print("Server is ready!")
+                return True
+        except requests.exceptions.ConnectionError:
+            pass
+        time.sleep(2)
+        print(".", end="", flush=True)
+    print("\nServer timed out.")
+    return False
+
+def test_recommendation():
+    if not os.path.exists(IMAGE_PATH):
+        print(f"Test image not found at {IMAGE_PATH}")
+        return
+
+    print(f"Testing recommendation with {IMAGE_PATH}...")
+    try:
+        with open(IMAGE_PATH, "rb") as f:
+            files = {"file": f}
+            response = requests.post(f"{API_URL}/recommend", files=files)
+        
+        if response.status_code == 200:
+            print("Success!")
+            print(response.json())
+        else:
+            print(f"Failed: {response.status_code}")
+            print(response.text)
+    except Exception as e:
+        print(f"Error: {e}")
+
+if __name__ == "__main__":
+    if wait_for_server():
+        test_recommendation()
+    else:
+        sys.exit(1)

test_results.txt

@@ -0,0 +1,12 @@
+Starting simple accuracy test...
+Classes found: ['Heart', 'Oblong', 'Oval', 'Round', 'Square']
+Testing Heart with ../dataset/test/Heart/Heart(0).jpg
+Result for Heart: {'oblong': 0.2003, 'heart': 0.2001, 'square': 0.2001, 'oval': 0.2, 'round': 0.1995}
+Testing Oblong with ../dataset/test/Oblong/Oblong(0).jpg
+Result for Oblong: {'square': 0.2005, 'heart': 0.2001, 'oval': 0.2001, 'oblong': 0.2, 'round': 0.1992}
+Testing Oval with ../dataset/test/Oval/Oval(0).jpg
+Result for Oval: {'square': 0.2013, 'oblong': 0.2005, 'heart': 0.2002, 'oval': 0.2001, 'round': 0.1979}
+Testing Round with ../dataset/test/Round/Round(0).jpg
+Result for Round: {'square': 0.2005, 'oblong': 0.2002, 'oval': 0.2002, 'round': 0.1996, 'heart': 0.1995}
+Testing Square with ../dataset/test/Square/Square(0).jpg
+Result for Square: {'heart': 0.2005, 'oval': 0.2003, 'round': 0.1999, 'square': 0.1998, 'oblong': 0.1995}

train.py

@@ -0,0 +1,120 @@
+import os
+import cv2
+import numpy as np
+import pickle
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score, classification_report
+from sklearn.preprocessing import LabelEncoder
+
+# Configuration
+DATASET_DIR = "/home/codernotme/Projects/Github/katariaoptics/dataset"
+MODEL_PATH = "/home/codernotme/Projects/Github/katariaoptics/ai_service/face_shape_model.pkl"
+IMG_SIZE = (64, 64)  # Resize detected faces to this size
+
+# Load Haar Cascade for face detection
+cascade_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
+face_cascade = cv2.CascadeClassifier(cascade_path)
+
+def load_dataset():
+    images = []
+    labels = []
+    
+    # Expected classes
+    classes = ["heart", "oblong", "oval", "round", "square"]
+    
+    print(f"Loading dataset from {DATASET_DIR}...")
+    
+    for label in classes:
+        folder_path = os.path.join(DATASET_DIR, label)
+        if not os.path.isdir(folder_path):
+            print(f"Warning: Folder {folder_path} not found.")
+            continue
+            
+        print(f"Processing class: {label}")
+        count = 0
+        total_files = len(os.listdir(folder_path))
+        
+        for i, filename in enumerate(os.listdir(folder_path)):
+            if i % 50 == 0:
+                print(f"  Processed {i}/{total_files} images...")
+                
+            img_path = os.path.join(folder_path, filename)
+            try:
+                # Read image
+                img = cv2.imread(img_path)
+                if img is None:
+                    continue
+                
+                # Resize if huge to speed up detection
+                h, w = img.shape[:2]
+                if w > 1000:
+                    scale = 1000 / w
+                    img = cv2.resize(img, (1000, int(h * scale)))
+                
+                # Convert to grayscale
+                gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+                
+                # Detect faces
+                faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+                
+                # If face detected, crop and use it
+                if len(faces) > 0:
+                    # Use the largest face
+                    (x, y, w, h) = max(faces, key=lambda f: f[2] * f[3])
+                    face_roi = gray[y:y+h, x:x+w]
+                    
+                    # Resize and flatten
+                    resized = cv2.resize(face_roi, IMG_SIZE)
+                    flat_features = resized.flatten()
+                    
+                    images.append(flat_features)
+                    labels.append(label)
+                    count += 1
+            except Exception as e:
+                print(f"Error processing {img_path}: {e}")
+                
+        print(f"  Loaded {count} images for {label}")
+        
+    return np.array(images), np.array(labels)
+
+def train_model():
+    X, y = load_dataset()
+    
+    if len(X) == 0:
+        print("Error: No images loaded. Dataset might be empty or paths incorrect.")
+        return
+
+    print(f"Total dataset size: {len(X)} samples")
+
+    # Encode labels
+    le = LabelEncoder()
+    y_encoded = le.fit_transform(y)
+    
+    # Save label encoder classes for inference
+    with open(MODEL_PATH.replace(".pkl", "_classes.pkl"), "wb") as f:
+        pickle.dump(le.classes_, f)
+    print(f"Saved class labels: {le.classes_}")
+
+    # Split dataset
+    X_train, X_test, y_train, y_test = train_test_split(X, y_encoded, test_size=0.2, random_state=42)
+    
+    # Train Random Forest
+    print("Training Random Forest Classifier...")
+    clf = RandomForestClassifier(n_estimators=100, random_state=42)
+    clf.fit(X_train, y_train)
+    
+    # Evaluate
+    y_pred = clf.predict(X_test)
+    accuracy = accuracy_score(y_test, y_pred)
+    print(f"Model Accuracy: {accuracy * 100:.2f}%")
+    print("\nClassification Report:")
+    print(classification_report(y_test, y_pred, target_names=le.classes_))
+    
+    # Save model
+    with open(MODEL_PATH, "wb") as f:
+        pickle.dump(clf, f)
+    print(f"Model saved to {MODEL_PATH}")
+
+if __name__ == "__main__":
+    train_model()

train_means.py

@@ -0,0 +1,62 @@
+import os
+import pickle
+import numpy as np
+from PIL import Image
+
+# Configuration
+# Use local paths relative to the script location
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+DATASET_DIR = os.environ.get("DATASET_DIR", os.path.join(BASE_DIR, "dataset"))
+MODEL_PATH = os.environ.get("MODEL_PATH", os.path.join(BASE_DIR, "face_shape_means.pkl"))
+IMG_SIZE = (64, 64)
+
+
+def load_and_compute_means():
+    classes = ["heart", "oblong", "oval", "round", "square"]
+    class_means = {}
+    
+    print(f"Dataset Dir: {DATASET_DIR}")
+    
+    for label in classes:
+        folder_path = os.path.join(DATASET_DIR, label)
+        if not os.path.isdir(folder_path):
+            print(f"Warning: Folder {folder_path} not found")
+            continue
+            
+        print(f"Processing {label}...")
+        vectors = []
+        
+        files = os.listdir(folder_path)
+        total = len(files)
+        
+        for i, filename in enumerate(files):
+            if i % 100 == 0:
+                print(f"  {i}/{total}")
+
+            try:
+                img_path = os.path.join(folder_path, filename)
+                with Image.open(img_path) as img:
+                    # Convert to grayscale and resize
+                    img = img.convert("L").resize(IMG_SIZE)
+                    # Flatten
+                    arr = np.array(img).flatten()
+                    vectors.append(arr)
+            except Exception as e:
+                # print(f"Error {filename}: {e}")
+                pass
+        
+        if vectors:
+            # Compute mean vector for this class
+            mean_vector = np.mean(vectors, axis=0)
+            class_means[label] = mean_vector
+            print(f"Computed mean for {label} from {len(vectors)} images.")
+        else:
+            print(f"No valid images for {label}!")
+
+    # Save means
+    with open(MODEL_PATH, "wb") as f:
+        pickle.dump(class_means, f)
+    print(f"Saved mean vectors to {MODEL_PATH}")
+
+if __name__ == "__main__":
+    load_and_compute_means()

train_model.py

@@ -0,0 +1,88 @@
+import os
+import cv2
+import glob
+import numpy as np
+import joblib
+from sklearn.model_selection import train_test_split
+from sklearn.svm import SVC
+from sklearn.preprocessing import LabelEncoder, StandardScaler
+from sklearn.pipeline import make_pipeline
+from sklearn.metrics import classification_report
+
+from landmarks import get_landmarks
+from geometry import extract_features
+
+DATASET_DIR = "../dataset"
+MODEL_PATH = "face_shape_model.pkl"
+
+def get_feature_vector(features):
+    """Converts feature dictionary to a list for the model."""
+    return [
+        features["lw_ratio"],
+        features["jaw_ratio"],
+        features["forehead_ratio"],
+        # Add more if geometry.py calculates them
+    ]
+
+def train():
+    print("Starting training...")
+    X = []
+    y = []
+    
+    # Iterate through each subdirectory in the dataset
+    # Assumes structure: dataset/ShapeName/image.jpg
+    if not os.path.exists(DATASET_DIR):
+        print(f"Dataset directory not found: {DATASET_DIR}")
+        return
+
+    classes = [d for d in os.listdir(DATASET_DIR) if os.path.isdir(os.path.join(DATASET_DIR, d))]
+    print(f"Found classes: {classes}")
+
+    for label in classes:
+        class_dir = os.path.join(DATASET_DIR, label)
+        image_files = glob.glob(os.path.join(class_dir, "*"))
+        
+        # Normalize label to capitalized format (e.g., "oval" -> "Oval") to match recommendation engine keys
+        normalized_label = label.capitalize()
+        
+        print(f"Processing {label} (normalized to {normalized_label}): {len(image_files)} images")
+        
+        for img_path in image_files:
+            try:
+                landmarks = get_landmarks(img_path)
+                feats = extract_features(landmarks)
+                vector = get_feature_vector(feats)
+                
+                X.append(vector)
+                y.append(normalized_label)
+            except Exception as e:
+                # print(f"Skipping {img_path}: {e}")
+                pass
+
+    if len(X) == 0:
+        print("No valid data found. Check dataset and landmarks extraction.")
+        return
+
+    X = np.array(X)
+    y = np.array(y)
+
+    print(f"Training on {len(X)} samples...")
+
+    # Train/Test split
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+    # Pipeline: Scale features -> SVM Classifier
+    model = make_pipeline(StandardScaler(), SVC(kernel='rbf', probability=True))
+    model.fit(X_train, y_train)
+
+    # Evaluate
+    print("Evaluating model...")
+    predictions = model.predict(X_test)
+    print(classification_report(y_test, predictions))
+
+    # Save
+    joblib.dump(model, MODEL_PATH)
+    print(f"Model saved to {MODEL_PATH}")
+
+if __name__ == "__main__":
+    train()

verify_simple.py

@@ -0,0 +1,27 @@
+import os
+import sys
+from detect import detect_face_shape
+
+# Add current dir to path logic if needed, but running from ai_service should be fine
+print("Starting simple verification...")
+
+DATASET_DIR = "../dataset"
+# Pick a file
+if os.path.exists(DATASET_DIR):
+    heart_dir = os.path.join(DATASET_DIR, "heart")
+    if os.path.exists(heart_dir):
+        files = os.listdir(heart_dir)
+        if files:
+            img_path = os.path.join(heart_dir, files[0])
+            print(f"Testing {img_path}")
+            try:
+                result = detect_face_shape(img_path)
+                print(f"Result: {result}")
+            except Exception as e:
+                print(f"Error: {e}")
+        else:
+            print("No files in heart dir")
+    else:
+        print("No heart dir")
+else:
+    print("No dataset dir")