puhuilab commited on
Commit
942ab45
·
verified ·
1 Parent(s): 35875c6

Upload folder using huggingface_hub

Browse files
Files changed (4) hide show
  1. .gitattributes +1 -1
  2. README.md +17 -2
  3. README_CN.md +15 -3
  4. vis.gif +3 -0
.gitattributes CHANGED
@@ -64,4 +64,4 @@ resources/fonts/方正宋黑.TTF filter=lfs diff=lfs merge=lfs -text
64
  resources/fonts/japan.ttc filter=lfs diff=lfs merge=lfs -text
65
  resources/fonts/FZYTK.TTF filter=lfs diff=lfs merge=lfs -text
66
  resources/fonts/korean.ttf filter=lfs diff=lfs merge=lfs -text
67
- resources/fonts/方正宋黑.TTF filter=lfs diff=lfs merge=lfs -text
 
64
  resources/fonts/japan.ttc filter=lfs diff=lfs merge=lfs -text
65
  resources/fonts/FZYTK.TTF filter=lfs diff=lfs merge=lfs -text
66
  resources/fonts/korean.ttf filter=lfs diff=lfs merge=lfs -text
67
+ resources/fonts/方正宋黑.TTF filter=lfs diff=lfs merge=lfs -textvis.gif filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -31,11 +31,23 @@ Current token-prediction-based model architectures are highly sensitive to the a
31
 
32
  ## Visualization
33
 
34
- ![Visualization](./vis.gif)
35
-
36
  ## Installation
37
 
38
  ```bash
 
 
 
 
 
 
 
 
 
 
 
 
 
 
39
  pip install phocr
40
  ```
41
 
@@ -54,6 +66,9 @@ print(result)
54
  # Visualize results
55
  result.vis("output.jpg")
56
  print(result.to_markdown())
 
 
 
57
  ```
58
 
59
  ## Benchmarks
 
31
 
32
  ## Visualization
33
 
 
 
34
  ## Installation
35
 
36
  ```bash
37
+ # Choose **one** installation method below:
38
+
39
+ # Method 1: Install with ONNX Runtime CPU version
40
+ pip install phocr[cpu]
41
+
42
+ # Method 2: Install with ONNX Runtime GPU version
43
+ pip install phocr[cuda]
44
+ # Required: Make sure the CUDA toolkit and cuDNN library are properly installed
45
+ # You can install cuda runtime and cuDNN via conda:
46
+ conda install -c nvidia cuda-runtime=12.1 cudnn=9
47
+ # Or manually install the corresponding CUDA toolkit and cuDNN libraries
48
+
49
+ # Method 3: Manually manage ONNX Runtime
50
+ # You can install `onnxruntime` or `onnxruntime-gpu` yourself, then install PHOCR
51
  pip install phocr
52
  ```
53
 
 
66
  # Visualize results
67
  result.vis("output.jpg")
68
  print(result.to_markdown())
69
+
70
+ ## only recognition
71
+
72
  ```
73
 
74
  ## Benchmarks
README_CN.md CHANGED
@@ -32,11 +32,22 @@ PHOCR 是一个高性能的开源光学字符识别(OCR)工具包,专为
32
 
33
  ## 可视化效果
34
 
35
- ![可视化效果](./vis.gif)
36
-
37
  ## 安装方式
38
-
39
  ```bash
 
 
 
 
 
 
 
 
 
 
 
 
 
 
40
  pip install phocr
41
  ```
42
 
@@ -55,6 +66,7 @@ print(result)
55
  # 可视化结果
56
  result.vis("output.jpg")
57
  print(result.to_markdown())
 
58
  ```
59
 
60
  ## 性能基准测试
 
32
 
33
  ## 可视化效果
34
 
 
 
35
  ## 安装方式
 
36
  ```bash
37
+ # 请选择以下 **一种** 安装方式:
38
+
39
+ # 方法一:安装带 ONNX Runtime CPU 版本
40
+ pip install phocr[cpu]
41
+
42
+ # 方法二:安装带 ONNX Runtime GPU 版本
43
+ pip install phocr[cuda]
44
+ # 必须:确保已正确安装 CUDA Toolkit 和 cuDNN 库
45
+ # 你可以通过 conda 安装 cuda-runtime和cuDNN:
46
+ conda install -c nvidia cuda-runtime=12.1 cudnn=9
47
+ # 或者手动安装对应版本的 CUDA Toolkit 和 cuDNN 库
48
+
49
+ # 方法三:手动管理 ONNX Runtime
50
+ # 你可以自行安装 `onnxruntime` 或 `onnxruntime-gpu`,然后再安装 PHOCR
51
  pip install phocr
52
  ```
53
 
 
66
  # 可视化结果
67
  result.vis("output.jpg")
68
  print(result.to_markdown())
69
+
70
  ```
71
 
72
  ## 性能基准测试
vis.gif ADDED

Git LFS Details

  • SHA256: e65bc8f999e6ed13108030d6f98d714200bda59581b78fc27d96aba2b5b41565
  • Pointer size: 132 Bytes
  • Size of remote file: 1.4 MB