Update apply_net.py

apply_net.py

@@ -77,6 +77,7 @@ class InferenceAction(Action):
         super(InferenceAction, cls).add_arguments(parser)
         parser.add_argument("cfg", metavar="<config>", help="Config file")
         parser.add_argument("model", metavar="<model>", help="Model file")
+        logger.info(f"[DEBUG] DensePose output for input shape {human_img.shape}: {outputs}")
         parser.add_argument(
             "--opts",
             help="Modify config options using the command-line 'KEY VALUE' pairs",
@@ -273,18 +274,21 @@ class ShowAction(InferenceAction):
     ):
         import cv2
         import numpy as np
+        import os
+        
         visualizer = context["visualizer"]
         extractor = context["extractor"]
         # image_fpath = entry["file_name"]
         # logger.info(f"Processing {image_fpath}")
-        image = cv2.cvtColor(entry["image"], cv2.COLOR_BGR2GRAY)
-        image = np.tile(image[:, :, np.newaxis], [1, 1, 3])
+        image = entry["image"]  # Already in BGR
+        # image = cv2.cvtColor(entry["image"], cv2.COLOR_BGR2GRAY)
+        # image = np.tile(image[:, :, np.newaxis], [1, 1, 3])
         data = extractor(outputs)
         image_vis = visualizer.visualize(image, data)
 
         return image_vis
         entry_idx = context["entry_idx"] + 1
-        out_fname = './image-densepose/' + image_fpath.split('/')[-1]
+        out_fname = os.path.join('./image-densepose', os.path.basename(image_fpath))
         out_dir = './image-densepose'
         out_dir = os.path.dirname(out_fname)
         if len(out_dir) > 0 and not os.path.exists(out_dir):