Update app.py

app.py

@@ -20,22 +20,19 @@ templates = Jinja2Templates(directory="templates")
 
 
 def predict_yolo(image_path):
-    # Assuming you have a YOLO API endpoint that accepts an image and returns predictions
-    with open(image_path, "rb") as file:
-        files = {"file": file}
-        # Load a model
-        model = YOLO('yolov8n.pt')  # pretrained YOLOv8n model
+    # Load a model
+    model = YOLO('yolov8n.pt')  # pretrained YOLOv8n model
 
-        # Run batched inference on a list of images
-        results = model(image_path)  # return a list of Results objects
+    # Run batched inference on a list of images
+    results = model(image_path)  # return a list of Results objects
 
-        # Process results list
-        for result in results:
-            boxes = result.boxes  # Boxes object for bbox outputs
-            # masks = result.masks  # Masks object for segmentation masks outputs
-            # keypoints = result.keypoints  # Keypoints object for pose outputs
-            # probs = result.probs  # Probs object for classification outputs
-        predictions = boxes.json()
+    # Process results list
+    for result in results:
+        boxes = result.boxes  # Boxes object for bbox outputs
+        # masks = result.masks  # Masks object for segmentation masks outputs
+        # keypoints = result.keypoints  # Keypoints object for pose outputs
+        # probs = result.probs  # Probs object for classification outputs
+    predictions = boxes.json()
     return predictions