Update app.py
Browse files
app.py
CHANGED
@@ -1,28 +1,36 @@
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import os
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import io
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import PIL.Image
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import gradio as gr
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from gradio_client import Client, handle_file
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from gradio_client.client import re
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from numpy import array
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# 1. Load your HF token from env
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HF_TOKEN = os.getenv("HF_TOKEN") # export HF_TOKEN="hf_..."
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client = Client(
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"franciszzj/Leffa",
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hf_token=HF_TOKEN,
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) # Gradio Python client
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def virtual_tryon(
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person_path,
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garment_path,
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garment_type,
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):
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# Wrap file inputs so Gradio client uploads them correctly
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person_file = handle_file(
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garment_file = handle_file(garment_path)
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#
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result = client.predict(
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person_file, # Person Image
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garment_file, # Garment Image
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vt_model_type="viton_hd",
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vt_garment_type=garment_type,
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vt_repaint=False,
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api_name="/leffa_predict_vt",
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return result[0] # Gradio will download & display this file
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#
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def check_password(pw):
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return gr.update(visible=(pw == "supersecretpassword"))
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("## VIRTUAL TRY-ON DEMO")
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# Invisible password prompt and access button (minimized to zero size)
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with gr.Row(visible=False): # Invisible container
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password_box = gr.Textbox(type="password", label="Enter access code", visible=False, elem_id="password_box") # Invisible password field
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access_button = gr.Button("Unlock", visible=False, elem_id="access_button") # Invisible button
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btn.click(virtual_tryon, [src, ref, garment_type], out)
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access_button.click(fn=check_password, inputs=password_box, outputs=main_ui)
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demo.launch(
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share=True,
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show_error=True,
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pwa=True,
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)
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import os
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import io
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# Workaround for PIL/Gradio bug :contentReference[oaicite:13]{index=13}
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import PIL.Image
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import gradio as gr
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from gradio_client import Client, handle_file
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from gradio_client.client import re
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from numpy import array
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# 1. Load your HF token from env
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HF_TOKEN = os.getenv("HF_TOKEN") # export HF_TOKEN="hf_..."
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# 1) Connect to the Leffa Gradio app’s predict endpoint
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# Use the full "/call/predict" API path as shown on the View API page
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client = Client(
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"franciszzj/Leffa",
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hf_token=HF_TOKEN,
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) # Gradio Python client
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def virtual_tryon(
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person_path,
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garment_path,
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garment_type,
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):
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# 2) Wrap file inputs so Gradio client uploads them correctly
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person_file = handle_file(
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person_path
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) # handle_file uploads the image :contentReference[oaicite:6]{index=6}
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garment_file = handle_file(garment_path)
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# 3) Build inputs in the exact order shown on the “Use via API” page :contentReference[oaicite:7]{index=7}
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# 4) Call the named endpoint with handle_file inputs
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result = client.predict(
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person_file, # Person Image
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garment_file, # Garment Image
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vt_model_type="viton_hd",
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vt_garment_type=garment_type,
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vt_repaint=False,
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api_name="/leffa_predict_vt",)
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# result[0] is the generated image filepath on the server
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return result[0] # Gradio will download & display this file
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# 5) Gradio UI
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("")
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with gr.Row():
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with gr.Column():
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gr.Markdown("")
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src = gr.Image(sources="upload", type="filepath",
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label="Foto e personit")
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with gr.Column():
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gr.Markdown("")
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ref = gr.Image(sources="upload", type="filepath",
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label="Foto e veshjes")
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with gr.Column():
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gr.Markdown("")
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garment_type = gr.Radio(
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choices=[("Siper", "upper_body"),
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("Posht", "lower_body"), ("Komplet", "dresses")],
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value="upper_body",
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label="Lloji i veshjes",
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)
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with gr.Column():
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gr.Markdown("")
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out = gr.Image(type="filepath", label="Rezultati",)
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with gr.Row():
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btn = gr.Button("VISHU")
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btn.click(virtual_tryon, [src, ref, garment_type], out)
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demo.launch(
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share=True,
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show_error=True,
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pwa=True,
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)
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