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Update requirements1.txt
Browse files- requirements1.txt +58 -1
requirements1.txt
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@@ -283,4 +283,61 @@ class Florence2:
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fp.write(results[task])
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fp.write("\n")
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fp.write(f"Image Name :: <==> {item}")
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fp.write("\n")
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fp.write(results[task])
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fp.write("\n")
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fp.write(f"Image Name :: <==> {item}")
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fp.write("\n")
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import copy
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from transformers import AutoProcessor, AutoModelForCausalLM
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from PIL import Image
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import requests
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import utils
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model_id = 'microsoft/Florence-2-large'
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True).eval().cuda()
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processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
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utils.set_model_info(model, processor)
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from google.colab import drive
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drive.mount('/content/drive')
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path = "/content/pci complliance and Credit card Authorization forms Hand written - Copy.jpg"
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image = Image.open(path)
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image_rgb = Image.open(path).convert("RGB")
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image
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img_list = ["/content/images_ocr_image_3.jpg",
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"/content/images_ocr_image_2.jpg",
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"/content/images_ocr_image_1.jpg",
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"/content/images_ocr_image_4.png",
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"/content/pci complliance and Credit card Authorization forms Hand written - Copy.jpg",
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"/content/Charlemagne.png",
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"/content/Frederick II.png",
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"/content/Henry VIII.png",
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"/content/Louis XIV.png",
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"/content/William IV.png",
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"/content/pci complliance and Credit card Authorization forms Hand written - Copy.jpg"
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]
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for item in img_list:
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path = item
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image = Image.open(path)
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image_rgb = Image.open(path).convert("RGB")
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tasks = [utils.TaskType.CAPTION,
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utils.TaskType.DETAILED_CAPTION,
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utils.TaskType.MORE_DETAILED_CAPTION,]
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for task in tasks:
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results = utils.run_example(task, image_rgb)
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print(f'{task.value}{results[task]}')
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task = utils.TaskType.OCR
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results = utils.run_example(task, image_rgb)
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print('Detected Text: ', results[task])
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with open("/content/florenecre.txt", "a+" ) as fp:
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fp.write(results[task])
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fp.write("\n")
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fp.write("Image Name :: <==>",item,"==="*30,item)
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fp.write("\n")
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