update

app.py

@@ -60,9 +60,6 @@ if not os.path.exists("saved_models/u2net/u2net.pth"):
 # Get model checkpoints
 if not os.path.exists("./checkpoints/decavtonfifapretrain/"):
     os.system("wget -O ./checkpoints/decavtonfifapretrain.zip https://github.com/hasibzunair/vton-demo/releases/download/v1.0/decavtonfifapretrain.zip")
-    # Works locally
-    #os.system("sudo apt-get install zip unzip")
-    #os.system("unzip ./checkpoints/decavtonfifapretrain.zip -d ./checkpoints/")
     with zipfile.ZipFile('./checkpoints/decavtonfifapretrain.zip', 'r') as zip_ref:
         zip_ref.extractall('./checkpoints/')
 
@@ -95,10 +92,12 @@ def composite_background(img_mask, person_image_path, tryon_image_path):
 
 
 # Main inference function
-def inference(clothing_image, person_image, remove_bg, retrieve_bg):
+def inference(clothing_image, person_image, retrieve_bg):
     """
     Do try-on!
     """
+    remove_bg = "no"
+    
     # Read cloth and person images
     cloth = Image.open(clothing_image) # cloth
     person = Image.open(person_image) # person
@@ -166,16 +165,19 @@ def inference(clothing_image, person_image, remove_bg, retrieve_bg):
         return os.path.join("results/test/try-on/person.png")
 
 
-title = "Virtual Dressing Room"
-description = "This is a demo for image based virtual try-on. It generates a synthetic image of a person wearing a target clothing item. To use it, simply upload your clothing item and person images, or click one of the examples to load them. Read more at the links below."
+title = "Image based Virtual Try-On"
+description = "This is a demo for an image based virtual try-on system. It generates a synthetic image of a person wearing a target clothing item. To use it, simply upload your clothing item and person images, or click one of the examples to load them."
 article = "<p style='text-align: center'><a href='will_be_added' target='_blank'>Fill in Fabrics: Body-Aware Self-Supervised Inpainting for Image-Based Virtual Try-On (Under Review!)</a> | <a href='https://github.com/dktunited/fifa_demo' target='_blank'>Github</a></p>"
 thumbnail = None # "./pathtothumbnail.png"
 
+# todos
+# train model with background removed then add feature, also add remove_bg in inferene()
+# add gr.inputs.Radio(choices=["yes","no"], default="no", label="Remove background from the person image?") in inputs
+    
 gr.Interface(
     inference,
     [gr.inputs.Image(type='filepath', label="Clothing Image"),
      gr.inputs.Image(type='filepath', label="Person Image"),
-     gr.inputs.Radio(choices=["yes","no"], default="no", label="Remove background from the person image?"),
      gr.inputs.Radio(choices=["yes","no"], default="no", label="Retrieve original background from the person image?")],
     gr.outputs.Image(type="filepath", label="Predicted Output"),
     examples=[["./sample_images/1/cloth.jpg", "./sample_images/1/person.jpg"],