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import spaces |
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import PIL |
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from PIL import Image |
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from PIL import ImageDraw |
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import gradio as gr |
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import easyocr |
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@spaces.GPU |
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def process(img_path): |
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reader = easyocr.Reader(['en']) |
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results = reader.readtext(img_path) |
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ret = "" |
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rat = 0 |
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pim = PIL.Image.open(img_path) |
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draw = ImageDraw.Draw(pim) |
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p0, p1, p2, p3 = 0, 0, 0, 0 |
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for (bbox, txt, prob) in results: |
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if prob > rat: |
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ret = txt |
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rat = prob |
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p0, p1, p2, p3 = bbox |
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if rat != 0: |
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draw.line([*p0, *p1, *p2, *p3, *p0], fill = 'yellow', width = 2) |
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return [pim, ret] |
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title = '车架号识别展示' |
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description = '拖拽图片到识别区开始分析' |
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ip = gr.Image(sources = ['upload'], label = '上传图片', width = '100%', height = '40rem', type = 'filepath') |
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op = [gr.Image(sources = None, label = '处理结果', width = '100%', height = '40rem', type = 'pil'), gr.Textbox(show_label = False)] |
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css = """ |
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#component-2 div.progress-text.svelte-ls20lj.meta-text { visibility: hidden; } |
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""" |
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gif = gr.Interface(fn = process, inputs = ip, outputs = op, title = title, description = description, batch = False, css = css, flagging_mode='never') |
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gif.launch(ssr_mode=False) |
