Update app.py

app.py

@@ -109,7 +109,7 @@ def draw_predictions(boxes, labels, scores, img, score_threshold=0.5):
 
     img_bbox = draw_bounding_boxes(
         img,
-        boxes=torch.from_numpy(boxes_filtered),
+        boxes=boxes_filtered,
         labels=[f"{name}: {score:.2f}" for name, score in zip(label_names, scores_filtered)],
         colors=colors,
         width=4
@@ -154,7 +154,7 @@ def inference(image_path, model_name, bbox_threshold):
     mask = max_scores > bbox_threshold
     
     pred_boxes = torch.from_numpy(pred_boxes[0])
-    image_w, image_h = img.size
+    image_w, image_h = image.size
     
     pred_boxes_abs = pred_boxes.clone()
     pred_boxes_abs[:, 0] *= image_w
@@ -170,7 +170,7 @@ def inference(image_path, model_name, bbox_threshold):
     filtered_scores = max_scores.squeeze(0)[mask]
     filtered_labels = pred_labels.squeeze(0)[mask]
     
-    img_tensor = torch.from_numpy(np.array(img)).permute(2, 0, 1)
+    img_tensor = torch.from_numpy(np.array(image)).permute(2, 0, 1)
     
     return draw_predictions(filtered_boxes, filtered_labels, filtered_scores, img_tensor, score_threshold=bbox_threshold)