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from flask import Flask, request, jsonify |
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from PIL import Image |
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import requests |
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from io import BytesIO |
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from sklearn.cluster import KMeans |
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import numpy as np |
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app = Flask(__name__) |
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def extract_dominant_color(image_url): |
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try: |
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response = requests.get(image_url) |
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img = Image.open(BytesIO(response.content)).convert('RGB') |
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img = img.resize((100, 100)) |
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pixels = np.array(img).reshape(-1, 3) |
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kmeans = KMeans(n_clusters=1, random_state=0).fit(pixels) |
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dominant_color = kmeans.cluster_centers_[0].astype(int) |
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hex_color = '#{:02x}{:02x}{:02x}'.format(*dominant_color) |
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return hex_color |
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except Exception as e: |
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return str(e) |
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@app.route('/') |
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def index(): |
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return jsonify({ |
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"message": "Use /color?img=https://your-image.jpg to get dominant color." |
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}) |
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@app.route('/color') |
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def get_color(): |
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image_url = request.args.get('img') |
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if not image_url: |
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return jsonify({'error': 'Missing image URL ?img=xxx'}), 400 |
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hex_color = extract_dominant_color(image_url) |
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if hex_color.startswith('#'): |
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return jsonify({'RGB': hex_color}) |
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else: |
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return jsonify({'error': 'Failed to extract color', 'detail': hex_color}), 500 |
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if __name__ == '__main__': |
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app.run(host='0.0.0.0', port=7860) |
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