changed default threshold for kpt detections

app.py

@@ -244,13 +244,15 @@ def predict_pipeline(img_input,
 
         # Produce final image
         img_background = Image.fromarray(md_results.imgs[0]) # img_input or Image.fromarray(md_results.imgs[0])? 
-        # Image.fromarray(md_results.imgs[0]) --> (640, 479)
-        # img_input.size ---> (259, 194)
-        # pdb.set_trace()
+        # # Image.fromarray(md_results.imgs[0]) --> (640, 479)
+        # # img_input.size ---> (259, 194)
+
 
         # resize image to match  megadetector output
+        # img_background = img_input
         # g = (640 / max(img_background.size))  # gain
-        # img_background = img_background.resize((int(x * g) for x in img_background.size), Image.ANTIALIAS)  # resize
+        # img_background = img_background.resize((int(x * g) for x in img_background.size), 
+        #                                         Image.ANTIALIAS)  # resize
         for ic, (np_crop, kpts_crop) in enumerate(zip(list_crops,
                                                       list_kpts_per_crop)):
 
@@ -298,7 +300,7 @@ gr_str_labels_checkbox = gr.inputs.Checkbox(True,
 
 gr_slider_conf_bboxes = gr.inputs.Slider(0,1,.05,0.8,
                                         label='Set confidence threshold for animal detections')
-gr_slider_conf_keypoints = gr.inputs.Slider(0,1,.05,0,
+gr_slider_conf_keypoints = gr.inputs.Slider(0,1,.05,0.25,
                                             label='Set confidence threshold for keypoints')
 
 # Data viz