CPR Added

.gitignore

@@ -0,0 +1,4 @@
+__pycache__/*
+venv/*
+uploads/*
+runs/*

app.py

@@ -15,10 +15,15 @@ import requests
 import joblib
 import numpy as np
 from ECG import classify_new_ecg
+from ultralytics import YOLO
+import tensorflow as tf
+from fastapi import HTTPException
 
 
 app = FastAPI()
 
+UPLOAD_DIR = "uploads"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
 # ✅ MongoDB connection
 mongo_uri = "mongodb://husseinelhadidy03:W8ByXdBS4EFkZmd5@ac-lqfhgnk-shard-00-00.ycuagnj.mongodb.net:27017,ac-lqfhgnk-shard-00-01.ycuagnj.mongodb.net:27017,ac-lqfhgnk-shard-00-02.ycuagnj.mongodb.net:27017/?replicaSet=atlas-az5d0x-shard-0&ssl=true&authSource=admin&retryWrites=true&w=majority&appName=Cluster0"
 client = MongoClient(mongo_uri, server_api=ServerApi('1'))
@@ -136,7 +141,6 @@ def transform_image():
     except Exception as e:
         return {"error": str(e)}
     
-
 @app.post("/classify-ecg")
 async def classify_ecg(files: list[UploadFile] = File(...)):
     model = joblib.load('voting_classifier.pkl')
@@ -166,4 +170,35 @@ async def classify_ecg(files: list[UploadFile] = File(...)):
         for file_name in os.listdir(temp_dir):
             file_path = os.path.join(temp_dir, file_name)
             os.remove(file_path)
-        os.rmdir(temp_dir)
+        os.rmdir(temp_dir)
+
+
+@app.post("/process_video")
+async def process_video(file: UploadFile = File(...)):
+    if not file.content_type.startswith("video/"):
+        raise HTTPException(status_code=400, detail="File must be a video.")
+
+    print("File content type:", file.content_type)
+    print("File filename:", file.filename)
+    # Save uploaded file
+    video_path = os.path.join(UPLOAD_DIR, file.filename)
+    with open(video_path, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+
+    model = YOLO(r"C:\Users\husse\Desktop\All Courses\BackendElhaany\Deploy_El7a2ny_Application\yolo11n-pose_float16.tflite")  # fixed variable name
+
+    print("Model loaded successfully")
+
+    # Run YOLO detection
+    try:
+        results = model(
+            source=video_path,
+            show=True,     # Set True if running locally and want to view
+            save=True,
+            project="runs/detect",
+            name="testResult"
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"YOLO processing error: {str(e)}")
+
+    return JSONResponse(content={"message": "Video processed successfully", "result_dir": "runs/detect/testResult"})

main.py

@@ -15,10 +15,15 @@ import requests
 import joblib
 import numpy as np
 from ECG import classify_new_ecg
+from ultralytics import YOLO
+import tensorflow as tf
+from fastapi import HTTPException
 
 
 app = FastAPI()
 
+UPLOAD_DIR = "uploads"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
 # ✅ MongoDB connection
 mongo_uri = "mongodb://husseinelhadidy03:W8ByXdBS4EFkZmd5@ac-lqfhgnk-shard-00-00.ycuagnj.mongodb.net:27017,ac-lqfhgnk-shard-00-01.ycuagnj.mongodb.net:27017,ac-lqfhgnk-shard-00-02.ycuagnj.mongodb.net:27017/?replicaSet=atlas-az5d0x-shard-0&ssl=true&authSource=admin&retryWrites=true&w=majority&appName=Cluster0"
 client = MongoClient(mongo_uri, server_api=ServerApi('1'))
@@ -136,7 +141,6 @@ def transform_image():
     except Exception as e:
         return {"error": str(e)}
     
-
 @app.post("/classify-ecg")
 async def classify_ecg(files: list[UploadFile] = File(...)):
     model = joblib.load('voting_classifier.pkl')
@@ -166,4 +170,35 @@ async def classify_ecg(files: list[UploadFile] = File(...)):
         for file_name in os.listdir(temp_dir):
             file_path = os.path.join(temp_dir, file_name)
             os.remove(file_path)
-        os.rmdir(temp_dir)
+        os.rmdir(temp_dir)
+
+
+@app.post("/process_video")
+async def process_video(file: UploadFile = File(...)):
+    if not file.content_type.startswith("video/"):
+        raise HTTPException(status_code=400, detail="File must be a video.")
+
+    print("File content type:", file.content_type)
+    print("File filename:", file.filename)
+    # Save uploaded file
+    video_path = os.path.join(UPLOAD_DIR, file.filename)
+    with open(video_path, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+
+    model = YOLO(r"C:\Users\husse\Desktop\All Courses\BackendElhaany\Deploy_El7a2ny_Application\yolo11n-pose_float16.tflite")  # fixed variable name
+
+    print("Model loaded successfully")
+
+    # Run YOLO detection
+    try:
+        results = model(
+            source=video_path,
+            show=True,     # Set True if running locally and want to view
+            save=True,
+            project="runs/detect",
+            name="testResult"
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"YOLO processing error: {str(e)}")
+
+    return JSONResponse(content={"message": "Video processed successfully", "result_dir": "runs/detect/testResult"})

requirements.txt

@@ -1,21 +1,104 @@
-fastapi
-uvicorn[standard]
-pymongo[srv]
-python-multipart
-cloudinary
-numpy==1.26.4
-scikit-image
-scipy
-tensorly
-scikit-learn==1.2.2
-opencv-python
-matplotlib
-glob2
-requests
-wfdb
-PyWavelets
-xgboost
+absl-py==2.2.2
+aiohappyeyeballs==2.6.1
+aiohttp==3.11.16
+aiosignal==1.3.2
+annotated-types==0.7.0
+anyio==4.9.0
+astunparse==1.6.3
+async-timeout==5.0.1
+attrs==25.3.0
+certifi==2025.1.31
+cffi==1.17.1
+charset-normalizer==3.4.1
+click==8.1.8
+cloudinary==1.44.0
+colorama==0.4.6
+contourpy==1.3.2
+cycler==0.12.1
+dnspython==2.7.0
+exceptiongroup==1.2.2
+fastapi==0.115.12
+filelock==3.18.0
+flatbuffers==25.2.10
+fonttools==4.57.0
+frozenlist==1.6.0
+fsspec==2025.3.2
+gast==0.6.0
+google-pasta==0.2.0
+grpcio==1.71.0
+h11==0.14.0
+h5py==3.13.0
+idna==3.10
+imageio==2.37.0
+Jinja2==3.1.6
 joblib==1.4.2
-uuid
-
-
+keras==3.9.2
+kiwisolver==1.4.8
+lazy_loader==0.4
+libclang==18.1.1
+Markdown==3.8
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+matplotlib==3.10.1
+mdurl==0.1.2
+ml-dtypes==0.4.1
+mpmath==1.3.0
+multidict==6.4.3
+namex==0.0.8
+networkx==3.4.2
+numpy==2.0.2
+opencv-python==4.11.0.86
+opt_einsum==3.4.0
+optree==0.15.0
+packaging==25.0
+pandas==2.2.3
+pillow==11.2.1
+propcache==0.3.1
+protobuf==5.29.4
+psutil==7.0.0
+py-cpuinfo==9.0.0
+pycparser==2.22
+pydantic==2.11.3
+pydantic_core==2.33.1
+Pygments==2.19.1
+pymongo==4.12.0
+pyparsing==3.2.3
+python-dateutil==2.9.0.post0
+python-multipart==0.0.20
+pytz==2025.2
+PyWavelets==1.8.0
+PyYAML==6.0.2
+requests==2.32.3
+rich==14.0.0
+scikit-image==0.25.2
+scikit-learn==1.6.1
+scipy==1.15.2
+seaborn==0.13.2
+six==1.17.0
+sniffio==1.3.1
+soundfile==0.13.1
+starlette==0.46.2
+sympy==1.13.1
+tensorboard==2.18.0
+tensorboard-data-server==0.7.2
+tensorflow==2.18.0
+tensorflow-io-gcs-filesystem==0.31.0
+tensorflow_intel==2.18.0
+tensorly==0.9.0
+termcolor==3.0.1
+threadpoolctl==3.6.0
+tifffile==2025.3.30
+torch==2.6.0
+torchvision==0.21.0
+tqdm==4.67.1
+typing-inspection==0.4.0
+typing_extensions==4.13.2
+tzdata==2025.2
+ultralytics==8.3.111
+ultralytics-thop==2.0.14
+urllib3==2.4.0
+uvicorn==0.34.2
+Werkzeug==3.1.3
+wfdb==4.3.0
+wrapt==1.17.2
+yarl==1.20.0