Update app.py

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,denoise_steps,seed, category):
     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', "upper_body", model_parse, keypoints)
+        mask, mask_gray = get_mask_location('hd', category, model_parse, keypoints)
         mask = mask.resize((768,1024))
     else:
         mask = pil_to_binary_mask(dict['layers'][0].convert("RGB").resize((768, 1024)))
@@ -275,6 +275,9 @@ with image_blocks as demo:
                 examples_per_page=10,
                 examples=human_ex_list
             )
+        
+        with gr.Column():
+            category = gr.Textbox(placeholder="0 = upper body, 1 = lower body, 2 = full body", show_label=False, elem_id="prompt")
 
         with gr.Column():
             garm_img = gr.Image(label="Garment", sources='upload', type="pil")
@@ -304,7 +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, denoise_steps, seed, category], outputs=[image_out,masked_img], api_name='tryon')