restore the code

app.py

@@ -1,72 +1,18 @@
 import subprocess
 import sys
 
+from transformers import AutoTokenizer
+import numpy as np
+from torchvision import transforms
+
+
 # Install gradio manually
-print(">>>Start of the building")
 subprocess.check_call([sys.executable, "-m", "pip", "install", "gradio"])
-print(">>>Step started!")
 import gradio as gr
 
 def greet(name):
     return "Hello " + name + "!!"
 
-def start_tryon():
-    return "Hello " + "**" + "!!"
-
-# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-# iface.launch()
-
-
-human_ex_list = []
-for ex_human in human_ex_list:
-    ex_dict = {}
-    ex_dict['background'] = ex_human
-    ex_dict['layers'] = None
-    ex_dict['composite'] = None
-    human_ex_list.append(ex_dict)
-
-## default human
-
-image_blocks = gr.Blocks().queue()
-
-with image_blocks as demo:
-    gr.Markdown("## Virtual Try On")
-    gr.Markdown("Virtual Try -n with your image and garment image.")
-    with gr.Row():
-        with gr.Column():
-            imgs = gr.ImageEditor(sources='upload', type='pil', label='Human, Mask with pen or use auto-masking', interactive=True)
-            with gr.Row():
-                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)
-            ### EXAMPLE TODO
-            example = gr.Examples(
-                inputs=imgs,
-                example_per_page=10,
-                examples=human_ex_list
-            )
-        
-        with gr.Column():
-            garm_img = gr.Image(label="Garment", sources='upload', type='pil')
-            with gr.Row(elem_id="promt-container"):
-                prompt = gr.Textbox(placeholder="Description of garment ex) Short Sleeve Round Neck T-shirts", show_label=False, elem_id="prompt")
-            ### EXAPLE TODO
-        
-        with gr.Column():
-            masked_img = gr.Image(label="Masked iamge output", elem_id="masked-img", show_share_button=False)
-        with gr.Column():
-            image_out = gr.Image(label="Output", elem_id="output-img", show_share_button=False)
-
-    with gr.Column():
-        try_button = gr.Button(value="Try-on")
-        with gr.Accordion(label = "Advanced Settings", open=False):
-            with gr.Row():
-                denoise_steps = gr.Number(label="Denoising Steps", minimum=20, maximum=40, value=30, step=1)
-                seed = gr.Number(label="Seed", minimum=-1, maximum=2147483647, step=1, value=42)
-
-    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')
-
 
-print("why")
-print("s")
-print("wtf")
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()