Update app.py
Browse files
app.py
CHANGED
@@ -5,6 +5,8 @@ import torch
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import numpy as np
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import io
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import base64
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app = Flask(__name__)
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@@ -12,6 +14,9 @@ app = Flask(__name__)
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processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
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model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
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# Function to process image and generate mask
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def process_image(image, prompt):
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inputs = processor(
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@@ -47,6 +52,11 @@ def get_masks(prompts, img, threshold):
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# Function to extract image using positive and negative prompts
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def extract_image(pos_prompts, neg_prompts, img, threshold):
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positive_masks = get_masks(pos_prompts, img, 0.5)
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negative_masks = get_masks(neg_prompts, img, 0.5)
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@@ -55,15 +65,16 @@ def extract_image(pos_prompts, neg_prompts, img, threshold):
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final_mask = pos_mask & ~neg_mask
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final_mask = Image.fromarray(final_mask.astype(np.uint8) * 255, "L")
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output_image = Image.new("RGBA", img.size, (0, 0, 0, 0))
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output_image.paste(img, mask=final_mask)
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# Convert final mask to base64
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buffered = io.BytesIO()
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final_mask.save(buffered, format="PNG")
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final_mask_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
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@app.route('/')
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def hello_world():
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@@ -84,10 +95,21 @@ def process_request():
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threshold = float(data.get('threshold', 0.4))
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# Perform image segmentation
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return jsonify(
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if __name__ == '__main__':
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print("Server starting. Verify it is running by visiting http://0.0.0.0:7860/")
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app.run(host='0.0.0.0', port=7860, debug=True)
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import numpy as np
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import io
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import base64
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import threading
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import time
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app = Flask(__name__)
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processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
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model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
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# Global variable for caching results
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cache = {}
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# Function to process image and generate mask
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def process_image(image, prompt):
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inputs = processor(
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# Function to extract image using positive and negative prompts
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def extract_image(pos_prompts, neg_prompts, img, threshold):
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cache_key = (pos_prompts, neg_prompts, threshold)
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if cache_key in cache:
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return cache[cache_key]
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positive_masks = get_masks(pos_prompts, img, 0.5)
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negative_masks = get_masks(neg_prompts, img, 0.5)
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final_mask = pos_mask & ~neg_mask
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final_mask = Image.fromarray(final_mask.astype(np.uint8) * 255, "L")
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# Convert final mask to base64
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buffered = io.BytesIO()
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final_mask.save(buffered, format="PNG")
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final_mask_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
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# Cache the result
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cache[cache_key] = {'final_mask_base64': final_mask_base64}
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return cache[cache_key]
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@app.route('/')
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def hello_world():
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threshold = float(data.get('threshold', 0.4))
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# Perform image segmentation
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result = extract_image(pos_prompts, neg_prompts, img, threshold)
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return jsonify(result)
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# Keep the server alive using a periodic task
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def keep_alive():
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while True:
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time.sleep(300) # 5 minutes
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requests.get('http://127.0.0.1:7860/') # Send a request to keep the server alive
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if __name__ == '__main__':
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print("Server starting. Verify it is running by visiting http://0.0.0.0:7860/")
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# Start the keep-alive thread
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keep_alive_thread = threading.Thread(target=keep_alive)
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keep_alive_thread.start()
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app.run(host='0.0.0.0', port=7860, debug=True)
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