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microsoft
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kosmos-2.5

Text2Text Generation
Transformers
Safetensors
English
kosmos-2.5
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Files changed (9) hide show
  1. README.md +83 -1
  2. config.json +151 -0
  3. generation_config.json +9 -0
  4. model-00001-of-00002.safetensors +3 -0
  5. model-00002-of-00002.safetensors +3 -0
  6. model.safetensors.index.json +621 -0
  7. preprocessor_config.json +5 -0
  8. tokenizer.json +0 -0
  9. tokenizer_config.json +10 -0
README.md CHANGED
@@ -2,6 +2,7 @@
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  language: en
3
  license: mit
4
  ---
 
5
 
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  # Kosmos-2.5
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@@ -16,6 +17,84 @@ Kosmos-2.5 is a multimodal literate model for machine reading of text-intensive
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  ## NOTE:
17
  Since this is a generative model, there is a risk of **hallucination** during the generation process, and it **CAN NOT** guarantee the accuracy of all OCR/Markdown results in the images.
18
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
 
20
  ## Citation
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@@ -33,4 +112,7 @@ If you find Kosmos-2.5 useful in your research, please cite the following paper:
33
  ## License
34
  The content of this project itself is licensed under the [MIT](https://github.com/microsoft/unilm/blob/master/kosmos-2.5/LICENSE)
35
 
36
- [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct)
 
 
 
 
2
  language: en
3
  license: mit
4
  ---
5
+ # Under testing
6
 
7
  # Kosmos-2.5
8
 
 
17
  ## NOTE:
18
  Since this is a generative model, there is a risk of **hallucination** during the generation process, and it **CAN NOT** guarantee the accuracy of all OCR/Markdown results in the images.
19
 
20
+ ## Use with transformers：
21
+ ```bash
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+ pip install git+https://github.com/tic-top/transformers.git
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+ ```
24
+ ```python
25
+ from PIL import Image
26
+ import requests
27
+ import torch
28
+ from transformers import AutoProcessor, AutoModelForVision2Seq
29
+ import re
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+
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+ repo = "kirp/kosmos2_5"
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+ device = "cuda:0"
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+ dtype = torch.bfloat16
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+ model = AutoModelForVision2Seq.from_pretrained(repo, device_map=device, torch_dtype=dtype)
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+ processor = AutoProcessor.from_pretrained(repo)
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+
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+ url = "https://huggingface.co/kirp/kosmos2_5/resolve/main/receipt_00008.png"
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+ image = Image.open(requests.get(url, stream=True).raw)
39
+ prompt = "<ocr>" # <md>
40
+
41
+ inputs = processor(text=prompt, images=image, return_tensors="pt")
42
+ height, width = inputs.pop("height"), inputs.pop("width")
43
+ raw_width, raw_height = image.size
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+ scale_height = raw_height / height
45
+ scale_width = raw_width / width
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+
47
+ inputs = {k: v.to(device) if v is not None else None for k, v in inputs.items()}
48
+ inputs["flattened_patches"] = inputs["flattened_patches"].to(dtype)
49
+
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+ generated_ids = model.generate(
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+ **inputs,
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+ max_new_tokens=1024,
53
+ )
54
+ generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
55
+
56
+ def postprocess(y, scale_height, scale_width):
57
+ y = y.replace(prompt, "")
58
+ if "<md>" in prompt:
59
+ return y
60
+ pattern = r"<bbox><x_\d+><y_\d+><x_\d+><y_\d+></bbox>"
61
+ bboxs_raw = re.findall(pattern, y)
62
+ lines = re.split(pattern, y)[1:]
63
+ bboxs = [re.findall(r"\d+", i) for i in bboxs_raw]
64
+ bboxs = [[int(j) for j in i] for i in bboxs]
65
+ info = ""
66
+ for i in range(len(lines)):
67
+ box = bboxs[i]
68
+ x0, y0, x1, y1 = box
69
+ if not (x0 >= x1 or y0 >= y1):
70
+ x0 = int(x0 * scale_width)
71
+ y0 = int(y0 * scale_height)
72
+ x1 = int(x1 * scale_width)
73
+ y1 = int(y1 * scale_height)
74
+ info += f"{x0},{y0},{x1},{y0},{x1},{y1},{x0},{y1},{lines[i]}"
75
+ return info
76
+
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+ output_text = postprocess(generated_text[0], scale_height, scale_width)
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+ print(output_text)
79
+ ```
80
+ ```text
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+ 55,595,71,595,71,629,55,629,1
82
+ 82,595,481,595,481,635,82,635,[REG] BLACK SAKURA
83
+ 716,590,841,590,841,629,716,629,45,455
84
+ 55,637,71,637,71,672,55,672,1
85
+ 82,637,486,637,486,675,82,675,COOKIE DOH SAUCES
86
+ 818,632,843,632,843,668,818,668,0
87
+ 51,683,71,683,71,719,51,719,1
88
+ 82,683,371,683,371,719,82,719,NATA DE COCO
89
+ 820,677,845,677,845,713,820,713,0
90
+ 32,770,851,770,851,811,32,811,Sub Total 45,455
91
+ 28,811,853,811,853,858,28,858,PB1 (10%) 4,545
92
+ 28,857,855,857,855,905,28,905,Rounding 0
93
+ 24,905,858,905,858,956,24,956,Total 50,000
94
+ 17,1096,868,1096,868,1150,17,1150,Card Payment 50,000
95
+ ```
96
+
97
+
98
 
99
  ## Citation
100
 
 
112
  ## License
113
  The content of this project itself is licensed under the [MIT](https://github.com/microsoft/unilm/blob/master/kosmos-2.5/LICENSE)
114
 
115
+ [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct)
116
+
117
+
118
+
config.json ADDED
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+ }
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+ }
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