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Add virtual try-on code
Browse files- app.py +56 -0
- requirements.txt +10 -0
app.py
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import gradio as gr
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from PIL import Image
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import os
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import torch
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import mediapipe as mp
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from transformers import SamModel, SamProcessor
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from diffusers.utils import load_image
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from torchvision import transforms
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# Load model once
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model = SamModel.from_pretrained("Zigeng/SlimSAM-uniform-50")
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processor = SamProcessor.from_pretrained("Zigeng/SlimSAM-uniform-50")
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def get_shoulder_coordinates(image: Image.Image):
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mp_pose = mp.solutions.pose
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pose = mp_pose.Pose()
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image_rgb = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
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results = pose.process(image_rgb)
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if results.pose_landmarks:
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height, width, _ = image_rgb.shape
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landmarks = results.pose_landmarks.landmark
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left = (int(landmarks[11].x * width), int(landmarks[11].y * height))
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right = (int(landmarks[12].x * width), int(landmarks[12].y * height))
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return left, right
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return None
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def try_on(person_img, tshirt_img):
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coordinates = get_shoulder_coordinates(person_img)
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if coordinates is None:
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return "No pose detected", None
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left_shoulder, right_shoulder = coordinates
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input_points = [[[left_shoulder[0], left_shoulder[1]], [right_shoulder[0], right_shoulder[1]]]]
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inputs = processor(person_img, input_points=input_points, return_tensors="pt")
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outputs = model(**inputs)
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masks = processor.image_processor.post_process_masks(outputs.pred_masks.cpu(),
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inputs["original_sizes"].cpu(),
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inputs["reshaped_input_sizes"].cpu())
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mask_tensor = masks[0][0][2].to(dtype=torch.uint8)
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mask = transforms.ToPILImage()(mask_tensor * 255)
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tshirt_img = tshirt_img.resize(person_img.size, Image.LANCZOS)
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result = Image.composite(tshirt_img, person_img, mask)
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return result
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demo = gr.Interface(fn=try_on,
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inputs=["image", "image"],
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outputs="image",
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title="Virtual Try-On using SlimSAM",
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description="Upload a person image and a t-shirt image.")
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demo.launch()
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requirements.txt
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Flask==2.3.3
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gunicorn==21.2.0
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Pillow==10.1.0
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opencv-python==4.9.0.80
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torch==2.2.0
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torchvision==0.17.0
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mediapipe==0.10.21
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transformers==4.40.1
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diffusers==0.27.2
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safetensors==0.4.2
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