Update ofa_ocr.py

ofa_ocr.py

@@ -25,60 +25,16 @@ def get_images(img: str, reader: ReaderLite, **kwargs):
     return results
 
 
-def draw_boxes(image, bounds, color='red', width=4):
-    draw = ImageDraw.Draw(image)
-    for i, bound in enumerate(bounds):
-        p0, p1, p2, p3 = bound
-        draw.text((p0[0]+5, p0[1]+5), str(i+1), fill=color, align='center')
-        draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
-    return image
-
 
 def ofa_ocr_gr():
     def ocr_api(img):
         results = get_images(img, reader, max_size=4000, text_confidence=0.7, text_threshold=0.4,
                              link_threshold=0.4, slope_ths=0., add_margin=0.04)
         box_list, image_list = zip(*results)
-        draw_boxes(img, box_list)
-
-        ocr_result = []
-        for i, (box, image) in enumerate(zip(box_list, image_list)):
-            image = Image.fromarray(image)
-            result = ocr_recognize(image)[OutputKeys.TEXT][0].replace(" ", "")
-            ocr_result.append([str(i + 1), result.replace(' ', '')])
-
-        result = pd.DataFrame(ocr_result, columns=['Box ID', 'Text'])
-
-        return img, result, box_list ##返回box_list 方便微调模型
-
-    examples = [
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/qiaodaima.png",
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/shupai.png",
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/ocr_essay.jpg",
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/chinese.jpg",
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/benpao.jpeg",
-        "http://xingchen-data.oss-cn-zhangjiakou.aliyuncs.com/maas/ocr/gaidao.jpeg",
-    ]
-
-    title = "<h1 align='center'>基于OFA的OCR识别的应用</h1>"
-    description = '中文OCR体验区，欢迎上传图片，静待检测文字返回~ 相关OCR代码和模型都已在ModelScope开源，支持finetune，欢迎大家在平台上使用！（注：受资源限制，这里只部署了通用OCR模型。）'
 
-    ocr_input_image = gr.components.Image(label='图片', type='pil')
+        return box_list ##返回box_list 方便作为api结果
 
-    ocr_output_image = gr.components.Image(label='图片')
-    ocr_output_text = gr.components.Dataframe(label='OCR结果', headers=['ID', '文本'])
 
-    ocr_demo = gr.Interface(
-        fn=ocr_api,
-        inputs=[ocr_input_image],
-        outputs=[ocr_output_image, ocr_output_text],
-        title=title,
-        description=description,
-        allow_flagging='never',
-        examples=examples,
-        examples_per_page=5,
-        cache_examples=False
-    )
 
     return ocr_api#返回子函数最后才能获取box ,至于ocr_demo这个gradio可有可无