Update app.py

app.py

@@ -3,36 +3,34 @@ from PIL import Image
 import os
 import sys
 
-# Make yolov12 folder importable
+# Add yolov12 folder to import path
 sys.path.append(os.path.abspath("yolov12"))
 
-# Import your YOLO class
-from yolo import YOLO  # Now from yolov12/yolo.py
+# Import your inference function
+from yolo import run_yolov12_inference
 
-# Load your custom YOLOv12 model
-model = YOLO("yolov12/best.pt")
+# Create temp upload dir
+UPLOAD_DIR = "static/uploaded"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
 
 def detect_damage(image: Image.Image):
-    results = model(image)
-
-    is_damaged = False
-    for result in results:
-        for box in result.boxes:
-            class_id = int(box.cls[0])
-            label = model.names[class_id]
-            print("Detected:", label)
-            if "apple_damaged" in label.lower():
-                is_damaged = True
-                break
+    # Save image to temp path
+    img_name = "test_image.jpg"
+    img_path = os.path.join(UPLOAD_DIR, img_name)
+    image.save(img_path)
+
+    # Run inference using your script
+    is_damaged = run_yolov12_inference(img_path)
 
     return {"is_damaged": is_damaged}
 
+# Gradio interface
 demo = gr.Interface(
     fn=detect_damage,
     inputs=gr.Image(type="pil"),
     outputs=gr.JSON(label="Detection Result"),
     title="🍎 Apple Damage Detector (YOLOv12)",
-    description="Upload an image of an apple to detect if it's damaged."
+    description="Upload an apple image to check if it's damaged using a custom YOLOv12 model."
 )
 
 demo.launch()