Added support for single image CPR

app.py

@@ -201,4 +201,36 @@ async def process_video(file: UploadFile = File(...)):
     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"})
+    return JSONResponse(content={"message": "Video processed successfully", "result_dir": "runs/detect/testResult"})
+
+
+@app.post("/process_image")
+async def process_image(file: UploadFile = File(...)):
+    if not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="File must be an image.")
+
+    print("File content type:", file.content_type)
+    print("File filename:", file.filename)
+
+    # Save uploaded image
+    image_path = os.path.join(UPLOAD_DIR, file.filename)
+    with open(image_path, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+
+    # Load the YOLO model
+    model = YOLO("yolo11n-pose_float16.tflite")
+
+    print("Model loaded successfully")
+
+    # Run YOLO detection on the image
+    try:
+        results = model(
+            source=image_path,
+            show=False,     # Set to False for API use
+            save=False
+        )
+        result_json = results[0].tojson()
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"YOLO processing error: {str(e)}")
+
+    return JSONResponse(content={"message": "Image processed successfully", "results": result_json})

main.py

@@ -189,7 +189,7 @@ async def process_video(file: UploadFile = File(...)):
 
     print("Model loaded successfully")
 
-    # Run YOLO detection
+    # Run YOLO detection 
     try:
         results = model(
             source=video_path,
@@ -201,4 +201,36 @@ async def process_video(file: UploadFile = File(...)):
     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"})
+    return JSONResponse(content={"message": "Video processed successfully", "result_dir": "runs/detect/testResult"})
+
+
+@app.post("/process_image")
+async def process_image(file: UploadFile = File(...)):
+    if not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="File must be an image.")
+
+    print("File content type:", file.content_type)
+    print("File filename:", file.filename)
+
+    # Save uploaded image
+    image_path = os.path.join(UPLOAD_DIR, file.filename)
+    with open(image_path, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+
+    # Load the YOLO model
+    model = YOLO("yolo11n-pose_float16.tflite")
+
+    print("Model loaded successfully")
+
+    # Run YOLO detection on the image
+    try:
+        results = model(
+            source=image_path,
+            show=False,     # Set to False for API use
+            save=False
+        )
+        result_json = results[0].tojson()
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"YOLO processing error: {str(e)}")
+
+    return JSONResponse(content={"message": "Image processed successfully", "results": result_json})