added checkbox for string labels (#12)

- added checkbox for string labels (14565b293b50b132aff7c6c680731528542bbb6d)

app.py

@@ -45,7 +45,8 @@ gr_dlc_model_input = gr.inputs.Dropdown(choices=['full_cat','full_dog', 'monkey_
                                         label='Select DeepLabCut model')
 gr_dlc_only_checkbox = gr.inputs.Checkbox(False,
                                          label='Run DLClive only, directly on input image?')                                        
-
+gr_str_labels_checkbox = gr.inputs.Checkbox(True,
+                                            label='Show bodypart labels?')   
 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,
@@ -67,16 +68,17 @@ gr_mega_model_input = gr.inputs.Dropdown(choices=['md_v5a','md_v5b'],
                                          type='value', # Type of value to be returned by component. "value" returns the string of the choice selected, "index" returns the index of the choice selected.
                                          label='Select MegaDetector model')
 inputs = [gr_image_input,
-                     gr_dlc_model_input,
-                     gr_dlc_only_checkbox,
-                     gr_slider_conf_bboxes,
-                     gr_slider_conf_keypoints,
-                     gr_pose_font_input,
-                     gr_slider_font_size, 
-                     gr_keypt_color,
-                     gr_slider_pose_size,
-                     gr_mega_model_input,
-                     ]                                                                                
+             gr_dlc_model_input,
+             gr_dlc_only_checkbox,
+             gr_str_labels_checkbox,
+             gr_slider_conf_bboxes,
+             gr_slider_conf_keypoints,
+             gr_pose_font_input,
+             gr_slider_font_size, 
+             gr_keypt_color,
+             gr_slider_pose_size,
+             gr_mega_model_input,
+             ]                                                                                
 
 #image = gr.inputs.Image(type="pil", label="Input Image")
 #chosen_model = gr.inputs.Dropdown(choices = models, value = "model_weights/md_v5a.0.0.pt",type = "value", label="Model Weight")
@@ -88,6 +90,7 @@ def draw_keypoints_on_image(image,
                             keypoints,
                             map_label_id_to_str,
                             use_normalized_coordinates=True,
+                            flag_show_str_labels,
                             gr_pose_font_input='amiko',
                             gr_slider_font_size=8,
                             gr_keypt_color="#ff0000",
@@ -125,11 +128,12 @@ def draw_keypoints_on_image(image,
                        outline=gr_keypt_color, fill=gr_keypt_color)
 
         # add string labels around keypoints
-        # draw.text((x, y),"Sample Text",(r,g,b))
-        draw.text((keypoint_x + gr_slider_pose_size, keypoint_y + gr_slider_pose_size),#(0.5*im_width, 0.5*im_height), #-------
-                  map_label_id_to_str[i],#"Sample Text",
-                  (gr_keypt_color), # rgb
-                  font=font)
+        if flag_show_str_labels:
+            # draw.text((x, y),"Sample Text",(r,g,b))
+            draw.text((keypoint_x + gr_slider_pose_size, keypoint_y + gr_slider_pose_size),#(0.5*im_width, 0.5*im_height), #-------
+                      map_label_id_to_str[i],#"Sample Text",
+                      (gr_keypt_color), # rgb
+                      font=font)
                     
 ############################################
 # %% 
@@ -222,6 +226,7 @@ def predict_dlc(list_np_crops,
 def predict_pipeline(img_input,
                      model_input_str,
                      flag_dlc_only,
+                     flag_show_str_labels,
                      bbox_likelihood_th,
                      kpts_likelihood_th,
                      gr_pose_font_input=gr_pose_font_input,
@@ -281,6 +286,7 @@ def predict_pipeline(img_input,
                                 list_kpts_per_crop[0], # a numpy array with shape [num_keypoints, 2].
                                 map_label_id_to_str,
                                 use_normalized_coordinates=False,
+                                flag_show_str_labels,
                                 gr_pose_font_input=gr_pose_font_input,
                                 gr_slider_font_size=gr_slider_font_size,
                                 gr_keypt_color=gr_keypt_color,
@@ -306,6 +312,7 @@ def predict_pipeline(img_input,
                                     kpts_crop, # a numpy array with shape [num_keypoints, 2].
                                     map_label_id_to_str,
                                     use_normalized_coordinates=False,  # if True, then I should use md_results.xyxyn
+                                    flag_show_str_labels,
                                     gr_pose_font_input=gr_pose_font_input,
                                     gr_slider_font_size=gr_slider_font_size,
                                     gr_keypt_color=gr_keypt_color,