Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| from gradio_client import Client | |
| import getpass # for secure token input | |
| # ----------------------------- | |
| # Prompt for Hugging Face API key | |
| # ----------------------------- | |
| API_KEY = getpass.getpass("Enter your Hugging Face API key: ").strip() | |
| try: | |
| hunyuan_client = Client("tencent/Hunyuan3D-2.1", hf_token=API_KEY) | |
| print("Hunyuan3D client loaded successfully!") | |
| except Exception as e: | |
| print(f"Failed to load Hunyuan3D client: {e}") | |
| hunyuan_client = None | |
| # ----------------------------- | |
| # Local "try-on" function | |
| # ----------------------------- | |
| def tryon_local(person_img, garment_img, seed, randomize_seed): | |
| if person_img is None or garment_img is None: | |
| return None, None, "Empty image" | |
| h_person, w_person = person_img.shape[:2] | |
| h_garment, w_garment = garment_img.shape[:2] | |
| scale = w_person / w_garment | |
| new_w = int(w_garment * scale) | |
| new_h = int(h_garment * scale) | |
| garment_resized = cv2.resize(garment_img, (new_w, new_h)) | |
| overlay = person_img.copy() | |
| y_offset = 0 | |
| x_offset = max(0, (w_person - new_w) // 2) | |
| if garment_resized.shape[2] == 4: | |
| alpha = garment_resized[:, :, 3] / 255.0 | |
| for c in range(3): | |
| overlay[y_offset:y_offset+new_h, x_offset:x_offset+new_w, c] = \ | |
| alpha * garment_resized[:, :, c] + (1 - alpha) * overlay[y_offset:y_offset+new_h, x_offset:x_offset+new_w, c] | |
| else: | |
| overlay[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = garment_resized | |
| info = "Success (local simulation)" | |
| return overlay, seed, info | |
| # ----------------------------- | |
| # Hunyuan3D API call | |
| # ----------------------------- | |
| def tryon_to_3d(person_img, garment_img, seed, randomize_seed): | |
| overlay_img, seed_used, info = tryon_local(person_img, garment_img, seed, randomize_seed) | |
| if overlay_img is None: | |
| return None, info | |
| if hunyuan_client is None: | |
| return overlay_img, "Hunyuan3D client not loaded" | |
| try: | |
| # Convert image to bytes to send via Gradio client | |
| _, img_encoded = cv2.imencode(".png", overlay_img) | |
| img_bytes = img_encoded.tobytes() | |
| # Predict with the client | |
| result = hunyuan_client.predict(img_bytes) | |
| return result, "Success (3D try-on)" | |
| except Exception as e: | |
| return overlay_img, f"Hunyuan3D API error: {e}" | |
| # ----------------------------- | |
| # Gradio UI | |
| # ----------------------------- | |
| css = """ | |
| #col-left, #col-mid, #col-right { | |
| margin: 0 auto; | |
| max-width: 430px; | |
| } | |
| #col-showcase { | |
| margin: 0 auto; | |
| max-width: 1100px; | |
| } | |
| #button { color: blue; } | |
| """ | |
| with gr.Blocks(css=css) as app: | |
| with gr.Row(): | |
| with gr.Column(elem_id="col-left"): | |
| person_input = gr.Image(label="Person Image", type="numpy") | |
| with gr.Column(elem_id="col-mid"): | |
| garment_input = gr.Image(label="Garment Image", type="numpy") | |
| with gr.Column(elem_id="col-right"): | |
| output_img = gr.Image(label="3D Result") | |
| result_info = gr.Text(label="Info") | |
| seed = gr.Slider(0, 999999, value=0, step=1, label="Seed") | |
| randomize_seed = gr.Checkbox(label="Random seed", value=True) | |
| run_btn = gr.Button("Run") | |
| run_btn.click( | |
| fn=tryon_to_3d, | |
| inputs=[person_input, garment_input, seed, randomize_seed], | |
| outputs=[output_img, result_info] | |
| ) | |
| app.launch() | |