test

app.py

@@ -70,6 +70,7 @@ def draw_keypoints_on_image(image,
     im_width, im_height = image.size
     keypoints_x = [k[0] for k in keypoints]
     keypoints_y = [k[1] for k in keypoints]
+    alpha = [k[2] for k in keypoints]
 
     # adjust keypoints coords if required
     if use_normalized_coordinates:
@@ -81,7 +82,8 @@ def draw_keypoints_on_image(image,
         draw.ellipse([(keypoint_x - marker_size, keypoint_y - marker_size),
                       (keypoint_x + marker_size, keypoint_y + marker_size)],
                        outline=keypt_color, 
-                       fill=keypt_color)
+                       fill=keypt_color,
+                       width=alpha[i])
 
         # add string labels around keypoints
         if flag_show_str_labels:
@@ -226,9 +228,7 @@ def predict_pipeline(img_input,
                                          kpts_likelihood_th,
                                          path_to_DLCmodel,
                                          dlc_proc)
-        # draw kpts on input img
-        print(list_kpts_per_crop)
-        print(list_kpts_per_crop[0])
+        # draw kpts on input img #fix!
         draw_keypoints_on_image(img_input,
                                 list_kpts_per_crop[0], # a numpy array with shape [num_keypoints, 2].
                                 map_label_id_to_str,
@@ -272,8 +272,7 @@ def predict_pipeline(img_input,
                                     keypt_color=keypt_color,
                                     marker_size=marker_size)
 
-            ## Paste crop in original image
-            # https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.paste
+            ## Paste crop in original image https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.paste
             img_background.paste(img_crop,
                                  box = tuple([int(t) for t in md_results.xyxy[0][ic,:2]]))