add mask area option

app.py

@@ -122,7 +122,7 @@ pipe = TryonPipeline.from_pretrained(
 pipe.unet_encoder = UNet_Encoder
 
 @spaces.GPU
-def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,denoise_steps,seed):
+def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,mask_area,denoise_steps,seed):
     device = "cuda"
     
     openpose_model.preprocessor.body_estimation.model.to(device)
@@ -150,7 +150,7 @@ def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,denoise_ste
     if is_checked:
         keypoints = openpose_model(human_img.resize((384,512)))
         model_parse, _ = parsing_model(human_img.resize((384,512)))
-        mask, mask_gray = get_mask_location('hd', "dresses", model_parse, keypoints)
+        mask, mask_gray = get_mask_location('hd', mask_area, model_parse, keypoints)
         mask = mask.resize((768,1024))
     else:
         mask = pil_to_binary_mask(dict['layers'][0].convert("RGB").resize((768, 1024)))
@@ -269,6 +269,8 @@ with image_blocks as demo:
                 is_checked = gr.Checkbox(label="Yes", info="Use auto-generated mask (Takes 5 seconds)",value=True)
             with gr.Row():
                 is_checked_crop = gr.Checkbox(label="Yes", info="Use auto-crop & resizing",value=False)
+            with gr.Row():
+                mask_area = gr.Radio(['upper_body', 'lower_body', 'dresses'], label="mask area", info="select what part to mask")
 
             example = gr.Examples(
                 inputs=imgs,
@@ -305,7 +307,7 @@ with image_blocks as demo:
 
 
 
-    try_button.click(fn=start_tryon, inputs=[imgs, garm_img, prompt, is_checked,is_checked_crop, denoise_steps, seed], outputs=[image_out,masked_img], api_name='tryon')
+    try_button.click(fn=start_tryon, inputs=[imgs, garm_img, prompt, is_checked,is_checked_crop,mask_area, denoise_steps, seed], outputs=[image_out,masked_img], api_name='tryon')