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Update app.py
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app.py
CHANGED
@@ -14,10 +14,8 @@ from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, Auto
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def save_temp_image(image: Image.Image) -> str:
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"""
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Saves the given PIL Image object as a temporary PNG file.
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-
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Args:
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image (Image.Image): The image to be saved.
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-
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Returns:
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str: The file path of the saved temporary image.
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"""
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@@ -34,13 +32,13 @@ def id_extractor(image: Image.Image) -> Dict:
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model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2.5-VL-
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)
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# default processer
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-
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messages = [
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@@ -106,8 +104,9 @@ def id_extractor(image: Image.Image) -> Dict:
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generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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)
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# Define the Gradio interface for the ID extractor
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id_interface = gr.Interface(
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fn=id_extractor,
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@@ -118,4 +117,4 @@ id_interface = gr.Interface(
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)
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# Launch the Gradio interface
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id_interface.launch(mcp_server=True)
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def save_temp_image(image: Image.Image) -> str:
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"""
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Saves the given PIL Image object as a temporary PNG file.
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Args:
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image (Image.Image): The image to be saved.
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Returns:
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str: The file path of the saved temporary image.
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"""
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model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2.5-VL-7B-Instruct", torch_dtype="auto", device_map="auto"
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)
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# default processer
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct")
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messages = [
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generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
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)
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resp = output_text[-1].replace("```json", "").replace("```", "").strip()
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return json.loads(resp)
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+
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# Define the Gradio interface for the ID extractor
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id_interface = gr.Interface(
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fn=id_extractor,
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)
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# Launch the Gradio interface
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id_interface.launch(mcp_server=True)
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