new try

app.py

@@ -13,38 +13,38 @@ model.conf = 0.20  # NMS confidence threshold
 
 path  = [['img/test-image.jpg'], ['img/test-image-2.jpg']]
 
-# def show_preds_image(image_path):
-#     image = cv2.imread(image_path)
-#     outputs = model.predict(source=image_path)
-#     results = outputs[0].cpu().numpy()
-#     for i, det in enumerate(results.boxes.xyxy):
-#         cv2.rectangle(
-#             image,
-#             (int(det[0]), int(det[1])),
-#             (int(det[2]), int(det[3])),
-#             color=(0, 0, 255),
-#             thickness=2,
-#             lineType=cv2.LINE_AA
-#         )
-#     return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-
 def show_preds_image(image_path):
-    # perform inference
-    image_path = path
-    results = model(image_path, size=640)
-    # Results
-    results.print()
+    image = cv2.imread(image_path)
+    outputs = model(source=image_path)
+    results = outputs[0].cpu().numpy()
+    for i, det in enumerate(results.boxes.xyxy):
+        cv2.rectangle(
+            image,
+            (int(det[0]), int(det[1])),
+            (int(det[2]), int(det[3])),
+            color=(0, 0, 255),
+            thickness=2,
+            lineType=cv2.LINE_AA
+        )
+    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+# def show_preds_image(image_path):
+#     # perform inference
+#     image_path = path
+#     results = model(image_path, size=640)
+#     # Results
+#     results.print()
 
-    results.xyxy[0]  # img1 predictions (tensor)
-    results.pandas().xyxy[0]  # img1 predictions (pandas)
+#     results.xyxy[0]  # img1 predictions (tensor)
+#     results.pandas().xyxy[0]  # img1 predictions (pandas)
 
-    # parse results
-    predictions = results.pred[0]
-    boxes = predictions[:, :4] # x1, y1, x2, y2
-    scores = predictions[:, 4]
-    categories = predictions[:, 5]
+#     # parse results
+#     predictions = results.pred[0]
+#     boxes = predictions[:, :4] # x1, y1, x2, y2
+#     scores = predictions[:, 4]
+#     categories = predictions[:, 5]
 
-    return results.show()
+#     return results.show()
 
     
 
@@ -58,7 +58,7 @@ interface_image = gr.Interface(
     fn=show_preds_image,
     inputs=inputs_image,
     outputs=outputs_image,
-    title="Pothole detector",
+    title="Cashew Disease Detection",
     examples=path,
     cache_examples=False,
 )