Spaces:
Running
Running
remove loadimg
Browse files- app.py +33 -25
- requirements.txt +2 -1
- results/.example +0 -0
app.py
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@@ -6,6 +6,7 @@ import base64
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import spaces
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from loadimg import load_img
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from PIL import Image
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title = """# 🙋🏻♂️Welcome to Tonic's🫴🏻📸GOT-OCR"""
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description = """"
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@@ -46,38 +47,45 @@ model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True,
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model = model.eval().cuda()
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model.config.pad_token_id = tokenizer.eos_token_id
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@spaces.GPU
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def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None, render=False):
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img = Image.open(img_path)
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else:
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img = Image.open(image)
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img_path = "/tmp/temp_image.png"
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img.save(img_path)
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if img_path.startswith("/tmp/"):
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os.remove(img_path)
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return res, None
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def update_inputs(task):
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if task == "Plain Text OCR" or task == "Format Text OCR" or task == "Multi-crop OCR":
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return [gr.update(visible=False)] * 4
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import spaces
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from loadimg import load_img
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from PIL import Image
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import numpy as np
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title = """# 🙋🏻♂️Welcome to Tonic's🫴🏻📸GOT-OCR"""
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description = """"
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model = model.eval().cuda()
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model.config.pad_token_id = tokenizer.eos_token_id
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def load_image(image_file):
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if isinstance(image_file, str):
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if image_file.startswith('http') or image_file.startswith('https'):
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return Image.open(requests.get(image_file, stream=True).raw).convert('RGB')
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else:
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return Image.open(image_file).convert('RGB')
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else:
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return image_file.convert('RGB')
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@spaces.GPU
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def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None, render=False):
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try:
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img = load_image(image)
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img_path = "/tmp/temp_image.png"
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img.save(img_path)
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if task == "Plain Text OCR":
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res = model.chat(tokenizer, img_path, ocr_type='ocr')
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elif task == "Format Text OCR":
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res = model.chat(tokenizer, img_path, ocr_type='format')
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elif task == "Fine-grained OCR (Box)":
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res = model.chat(tokenizer, img_path, ocr_type=ocr_type, ocr_box=ocr_box)
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elif task == "Fine-grained OCR (Color)":
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res = model.chat(tokenizer, img_path, ocr_type=ocr_type, ocr_color=ocr_color)
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elif task == "Multi-crop OCR":
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res = model.chat_crop(tokenizer, image_file=img_path)
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elif task == "Render Formatted OCR":
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res = model.chat(tokenizer, img_path, ocr_type='format', render=True, save_render_file='./results/demo.html')
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with open('./results/demo.html', 'r') as f:
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html_content = f.read()
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return res, html_content
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# Clean up
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os.remove(img_path)
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return res, None
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except Exception as e:
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return str(e), None
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def update_inputs(task):
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if task == "Plain Text OCR" or task == "Format Text OCR" or task == "Multi-crop OCR":
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return [gr.update(visible=False)] * 4
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requirements.txt
CHANGED
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@@ -8,4 +8,5 @@
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cairosvg
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accelerate
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numpy
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loadimg
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cairosvg
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accelerate
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numpy
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loadimg
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pillow
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results/.example
ADDED
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File without changes
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