Update README.md

README.md

@@ -7,4 +7,56 @@ pipeline_tag: image-to-text
 tags:
 - ocr
 - captcha
----
+---
+
+
+
+## 介绍（Introduction）
+**验证码识别模型（ocr-captcha）**专门识别常见验证码的模型，训练模型有2个：
+1.**small**:训练数据大小为700MB，约8.4万张验证码图片，训练轮次27轮，最终的精度将近100%，推荐下载这个模型；
+2.**big**:训练数据大小为11G，约135万个验证码图片，训练轮次1轮，最终的精度将近93.95%；
+
+
+## 快速使用（Quickstart）
+
+```python
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+import gradio as gr
+import os
+
+
+class xiaolv_ocr_model():
+
+    def __init__(self):
+        model_small = r"./output_small"
+        model_big = r"./output_big"
+        self.ocr_recognition_small = pipeline(Tasks.ocr_recognition, model=model_small)
+        self.ocr_recognition1_big = pipeline(Tasks.ocr_recognition, model=model_big)
+
+
+    def run(self,pict_path,moshi = "small", context=[]):
+        pict_path = pict_path.name
+        context = [pict_path]
+
+        if moshi == "small":
+            result = self.ocr_recognition_small(pict_path)
+        else:
+            result = self.ocr_recognition1_big(pict_path)
+
+        context += [str(result['text'][0])]
+        responses = [(u, b) for u, b in zip(context[::2], context[1::2])]
+        print(f"识别的结果为：{result}")
+        os.remove(pict_path)
+        return responses,context
+
+
+
+
+if __name__ == "__main__":
+    pict_path = r"C:\Users\admin\Desktop\图片识别测试\企业微信截图_16895911221007.png"
+    ocr_model = xiaolv_ocr_model()
+    # ocr_model.run(pict_path)
+```
+
+