app.py

import gradio as gr
import torch
import cv2
import numpy as np
from torchvision import transforms
from PIL import Image
from transformers import DPTForDepthEstimation, DPTFeatureExtractor
import torchvision.transforms.functional as F

# Load depth estimation model
model_name = "Intel/dpt-large"
feature_extractor = DPTFeatureExtractor.from_pretrained(model_name)
depth_model = DPTForDepthEstimation.from_pretrained(model_name)
depth_model.eval()

def estimate_depth(image):
    """Estimate depth map from image."""
    image = image.convert("RGB").resize((384, 384))  # Resize for model input
    inputs = feature_extractor(images=image, return_tensors="pt")
    with torch.no_grad():
        outputs = depth_model(**inputs)
        depth = outputs.predicted_depth.squeeze().cpu().numpy()
    depth = cv2.resize(depth, (image.width, image.height))  # Resize back
    depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255
    return depth.astype(np.uint8)

def warp_design(cloth_img, design_img):
    """Warp the design onto the clothing while preserving folds."""
    cloth_img = cloth_img.convert("RGB")
    design_img = design_img.convert("RGB")
    cloth_np = np.array(cloth_img)
    design_np = np.array(design_img)
    h, w, _ = cloth_np.shape
    
    # Estimate depth map
    depth_map = estimate_depth(cloth_img)
    depth_map = cv2.resize(depth_map, (w, h))
    
    # Compute optical flow for warping
    flow = cv2.calcOpticalFlowFarneback(depth_map, depth_map, None, 0.5, 3, 15, 3, 5, 1.2, 0)
    flow_map = np.column_stack((flow[..., 0] + np.arange(w), flow[..., 1] + np.arange(h)[:, None]))
    warped_design = cv2.remap(design_np, flow_map, None, cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)
    
    # Blending
    blended = cv2.addWeighted(cloth_np, 0.7, warped_design, 0.3, 0)
    
    return Image.fromarray(blended)

def main(cloth, design):
    return warp_design(cloth, design)

iface = gr.Interface(
    fn=main,
    inputs=[gr.Image(type="pil"), gr.Image(type="pil")],
    outputs=gr.Image(type="pil"),
    title="AI Cloth Design Warping",
    description="Upload a clothing image and a design to blend it naturally, ensuring it stays centered and follows fabric folds."
)

if __name__ == "__main__":
    iface.launch(share=True)