init commit

.gitattributes

@@ -0,0 +1,4 @@
+models/lbfmodel.yaml filter=lfs diff=lfs merge=lfs -text
+imgs/03.webp filter=lfs diff=lfs merge=lfs -text
+imgs/11.jpg filter=lfs diff=lfs merge=lfs -text
+imgs/people.jpg filter=lfs diff=lfs merge=lfs -text

.github/workflows/deploy-hf.yml

@@ -0,0 +1,25 @@
+name: Deploy to Hugging Face spaces
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout Dev Repo
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+
+      - name: Push to HF
+        env:
+          HFTOKEN: ${{ secrets.HFTOKEN }}
+
+        run: |
+          git remote add hf https://thiagohersan:$HFTOKEN@huggingface.co/spaces/visualizedata/PSAM5020-FaceAlign-Gradio
+          git push -f hf main

.gitignore

@@ -0,0 +1,5 @@
+.DS_S*
+__pycache__/
+gradio_cached_examples/
+.gradio/
+.ipynb_checkpoints/

README.md

@@ -0,0 +1,11 @@
+---
+title: PSAM5020 Face Align
+emoji: 📐
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+python_version: 3.10.12
+sdk_version: 5.0.2
+app_file: app.py
+pinned: false
+---

app.py

@@ -0,0 +1,108 @@
+import cv2
+import gradio as gr
+import numpy as np
+
+from huggingface_hub import hf_hub_download
+from math import atan2
+from PIL import Image as PImage
+from ultralytics import YOLO
+
+OUT_W = 130
+OUT_H = 170
+
+OUT_EYE_SPACE = 64
+OUT_FACE_WIDTH = 89
+OUT_NOSE_TOP = 72
+
+EYE_0_IDX = 36
+EYE_1_IDX = 45
+
+TEMPLE_0_IDX = 0
+TEMPLE_1_IDX = 16
+
+yolo_model_path = hf_hub_download(repo_id="AdamCodd/YOLOv11n-face-detection", filename="model.pt")
+face_detector = YOLO(yolo_model_path)
+
+LBFmodel = "./models/lbfmodel.yaml"
+landmark_detector  = cv2.face.createFacemarkLBF()
+landmark_detector.loadModel(LBFmodel)
+
+NUM_OUTS = 16
+all_outputs = [gr.Image(format="jpeg", visible=False) for _ in range(NUM_OUTS)]
+
+def face(img_in):
+  out_pad = NUM_OUTS * [gr.Image(visible=False)]
+  if img_in is None:
+    return out_pad
+
+  img = img_in.copy()
+  img.thumbnail((1000,1000))
+  img_np = np.array(img).copy()
+
+  iw,ih = img.size
+
+  output = face_detector.predict(img, verbose=False)
+
+  if len(output) < 1 or len(output[0]) < 1:
+    return out_pad
+
+  faces_xyxy = output[0].boxes.xyxy.numpy()
+  faces = np.array([[x0, y0, (x1 - x0), (y1 - y0)] for x0,y0,x1,y1 in faces_xyxy])
+
+  biggest_faces = faces[np.argsort(-faces[:,2])]
+  _, landmarks = landmark_detector.fit(img_np, biggest_faces)
+
+  if len(landmarks) < 1:
+    return out_pad
+
+  out_images = []
+  for landmark in landmarks:
+    eye0 = np.array(landmark[0][EYE_0_IDX])
+    eye1 = np.array(landmark[0][EYE_1_IDX])
+    temple0 = np.array(landmark[0][TEMPLE_0_IDX])
+    temple1 = np.array(landmark[0][TEMPLE_1_IDX])
+
+    mid = np.mean([eye0, eye1], axis=0)
+
+    eye_line = eye1 - eye0
+    tilt = atan2(eye_line[1], eye_line[0])
+    tilt_deg = 180 * tilt / np.pi
+
+
+    scale = min(OUT_EYE_SPACE / np.linalg.norm(eye1 - eye0),
+                OUT_FACE_WIDTH / np.linalg.norm(temple1 - temple0))
+
+    img_s = img.resize((int(iw * scale), int(ih * scale)))
+
+    # rotate around nose
+    new_mid = [int(c * scale) for c in mid]
+    crop_box = (new_mid[0] - (OUT_W // 2),
+                new_mid[1] - OUT_NOSE_TOP,
+                new_mid[0] + (OUT_W // 2),
+                new_mid[1] + (OUT_H - OUT_NOSE_TOP))
+
+    img_out = img_s.rotate(tilt_deg, center=new_mid, resample=PImage.Resampling.BICUBIC).crop(crop_box).convert("L")
+    out_images.append(gr.Image(img_out, visible=True))
+
+  out_images += out_pad
+  return out_images[:NUM_OUTS]
+
+
+with gr.Blocks() as demo:
+  gr.Markdown("""
+              # PSAM 5020 Face Alignment Tool.
+              ## Interface for face detection, alignment, cropping\
+              to help create dataset for [WK12](https://github.com/PSAM-5020-2025F-A/WK11) / [HW12](https://github.com/PSAM-5020-2025F-A/Homework11).
+              """)
+
+  gr.Interface(
+    face,
+    inputs=gr.Image(type="pil"),
+    outputs=all_outputs,
+    cache_examples=True,
+    examples=[["./imgs/03.webp"], ["./imgs/11.jpg"], ["./imgs/people.jpg"]],
+    allow_flagging="never",
+  )
+
+if __name__ == "__main__":
+   demo.launch()

models/lbfmodel.yaml

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

requirements.txt

@@ -0,0 +1,7 @@
+pydantic==2.8.2
+huggingface-hub==0.34.3
+opencv-python==4.10.0.84
+opencv-python-headless==4.10.0.84
+opencv-contrib-python==4.10.0.84
+opencv-contrib-python-headless==4.10.0.84
+ultralytics==8.3.102