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| import gradio as gr | |
| from PIL import Image, ImageDraw | |
| import yolov5 | |
| import json | |
| model = yolov5.load("./best.pt") | |
| def yolo(im): | |
| results = model(im) # inference | |
| df = results.pandas().xyxy[0].to_json(orient="records") | |
| res = json.loads(df) | |
| im_with_boxes = results.render()[0] # results.render() returns a list of images | |
| # Convert the numpy array back to an image | |
| output_image = Image.fromarray(im_with_boxes) | |
| draw = ImageDraw.Draw(im) | |
| for bb in res: | |
| xmin = bb['xmin'] | |
| ymin = bb['ymin'] | |
| xmax = bb['xmax'] | |
| ymax = bb['ymax'] | |
| draw.rectangle([xmin, ymin, xmax, ymax], outline="red", width=3) | |
| return [ | |
| output_image, | |
| res, | |
| im, | |
| ] | |
| inputs = gr.Image(type='pil', label="Original Image") | |
| outputs = [ | |
| gr.Image(type="pil", label="Output Image"), | |
| gr.JSON(label="Output JSON"), | |
| gr.Image(type='pil', label="Output Image with Boxes"), | |
| ] | |
| title = "YOLOv5 Character" | |
| description = "YOLOv5 Character Gradio demo for object detection. Upload an image or click an example image to use." | |
| article = "<p style='text-align: center'>YOLOv5 Character is an object detection model trained on the <a href=\"http://codh.rois.ac.jp/char-shape/\">日本古典籍くずし字データセット</a>.</p>" | |
| examples = [ | |
| ['『源氏物語』(東京大学総合図書館所蔵).jpg'], | |
| ['『源氏物語』(京都大学所蔵).jpg'], | |
| ['『平家物語』(国文学研究資料館提供).jpg'] | |
| ] | |
| demo = gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples) | |
| demo.css = """ | |
| .json-holder { | |
| height: 300px; | |
| overflow: auto; | |
| } | |
| """ | |
| demo.launch(share=False) |