input img components

app.py

@@ -131,7 +131,8 @@ def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,denoise_ste
 
     garm_img= garm_img.convert("RGB").resize((768,1024))
     
-    human_img_orig = dict["background"].convert("RGB")    
+    human_img_orig = dict.convert("RGB").resize((768,1024))
+    # human_img_orig = dict["background"].convert("RGB")    
     
     if is_checked_crop:
         width, height = human_img_orig.size
@@ -153,8 +154,8 @@ def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,denoise_ste
         model_parse, _ = parsing_model(human_img.resize((384,512)))
         mask, mask_gray = get_mask_location('hd', "upper_body", model_parse, keypoints)
         mask = mask.resize((768,1024))
-    else:
-        mask = pil_to_binary_mask(dict['layers'][0].convert("RGB").resize((768, 1024)))
+    # else:
+        # mask = pil_to_binary_mask(dict['layers'][0].convert("RGB").resize((768, 1024)))
         # mask = transforms.ToTensor()(mask)
         # mask = mask.unsqueeze(0)
     mask_gray = (1-transforms.ToTensor()(mask)) * tensor_transfrom(human_img)
@@ -265,7 +266,8 @@ with image_blocks as demo:
     gr.Markdown("Virtual Try-on with your image and garment image. Check out the [source codes](https://github.com/yisol/IDM-VTON) and the [model](https://huggingface.co/yisol/IDM-VTON)")
     with gr.Row():
         with gr.Column():
-            imgs = gr.ImageEditor(sources='upload', type="pil", label='Human. Mask with pen or use auto-masking', interactive=True)
+            # imgs = gr.ImageEditor(sources='upload', type="pil", label='Human. Mask with pen or use auto-masking', interactive=True)
+            imgs = gr.Image(label='Human', sources='upload', type="pil")
             garm_img = gr.Image(label="Garment", sources='upload', type="pil")
             with gr.Row(elem_id="prompt-container"):
                 with gr.Row():