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from PIL import Image |
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from transformers import AutoProcessor, AutoModelForVision2Seq |
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from flask import Flask, request, jsonify |
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app = Flask(__name__) |
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model = AutoModelForVision2Seq.from_pretrained("ydshieh/kosmos-2-patch14-224", trust_remote_code=True) |
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processor = AutoProcessor.from_pretrained("ydshieh/kosmos-2-patch14-224", trust_remote_code=True) |
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@app.route('/process_prompt', methods=['POST']) |
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def process_prompt(): |
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try: |
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uploaded_file = request.files['image'] |
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prompt = request.form.get('prompt') |
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image = Image.open(uploaded_file.stream) |
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inputs = processor(text=prompt, images=image, return_tensors="pt") |
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generated_ids = model.generate( |
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pixel_values=inputs["pixel_values"], |
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input_ids=inputs["input_ids"][:, :-1], |
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attention_mask=inputs["attention_mask"][:, :-1], |
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img_features=None, |
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img_attn_mask=inputs["img_attn_mask"][:, :-1], |
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use_cache=True, |
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max_new_tokens=64, |
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) |
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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processed_text, entities = processor.post_process_generation(generated_text) |
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return jsonify({"message": processed_text, 'entities': entities}) |
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except Exception as e: |
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return jsonify({"error": str(e)}) |
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if __name__ == '__main__': |
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app.run(host='localhost', port=8005) |
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