First model version

app.py

@@ -25,7 +25,7 @@ def infer(filepath):
     )
     image = cv2.imread(filepath)
     result_polygons, result_masks, result_boxes = det_demo.run_on_opencv_image(image)
-    image = det_demo.visualization(image, result_polygons, result_masks, result_boxes)
+    visual_image = det_demo.visualization(image, result_polygons, result_masks, result_boxes)
     cv2.imwrite('result.jpg', image)
     return 'result.jpg'#, pd.DataFrame(result_words)
 

det_demo.py

@@ -443,7 +443,7 @@ class DetDemo(object):
         prediction = prediction.resize((image_width, image_height))
         if len(prediction) == 0:
             return
-        prediction = prediction.convert("xywh")
+        prediction = prediction.convert("xyxy")
         boxes = prediction.bbox.tolist()
         scores = prediction.get_field("scores").tolist()
         masks_x = prediction.get_field("mask_x")
@@ -581,8 +581,7 @@ class DetDemo(object):
         for mask in masks:
             image[mask] = image[mask] * 0.5 + green[mask] * 0.5
         for box in boxes:
-            print(box)
-            cv2.rectangle(image,box,True,(0,0,255))
+            cv2.rectangle(image,(box[0], box[1]), (box[2], box[3]), (0,0,255), 5)
         '''
         for polygon in polygons:
             pts = np.array(polygon, np.int32)