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Runtime error
| from PIL import ImageFont, ImageDraw | |
| import numpy as np | |
| import gradio as gr | |
| import mim | |
| mim.install('mmcv-full==1.7.1') | |
| from mmcv.runner import load_checkpoint | |
| from mmdet.apis import inference_detector | |
| from mmdet.models import build_detector | |
| from cfg import cfg | |
| def show_results(org_image, results, classes, conf_threshold=0.2, classes_to_show=None): | |
| font = ImageFont.truetype("fonts/Bohemian_typewriter.ttf", 15) | |
| draw = ImageDraw.Draw(org_image) | |
| if classes_to_show is None: | |
| classes_to_show = list(np.arange(len(classes))) | |
| for i, res_class in enumerate(results): | |
| if i not in classes_to_show: | |
| continue | |
| for res in res_class: | |
| if res[4] > conf_threshold: | |
| draw.rectangle((res[0], res[1], res[2], res[3]), fill=None, outline="green", width=5) | |
| draw.text((res[0], res[1]), str(classes[i]), (0, 255, 0), font=font) | |
| return org_image | |
| def query_image(input_img): | |
| np_img = np.array(input_img)[:, :, ::-1].copy() | |
| result = inference_detector(model, np_img) | |
| pivot = 0 | |
| for res in result: | |
| if len(res) > 0: | |
| pivot = 1 | |
| break | |
| if pivot > 0: | |
| image_with_results = show_results(input_img, result, model.CLASSES, conf_threshold=0.2) | |
| else: | |
| image_with_results = input_img | |
| return image_with_results | |
| checkpoint = 'checkpoints/latest.pth' | |
| device = 'cpu' | |
| model = build_detector(cfg.model) | |
| checkpoint = load_checkpoint(model, checkpoint, map_location=device) | |
| model.CLASSES = checkpoint['meta']['CLASSES'] | |
| model.cfg = cfg | |
| model.to(device) | |
| model.eval() | |
| examples = ["images/DOPANAR_2_00009199.jpg", "images/2013_05_26_A_00000-00007_4_00016247.jpg", | |
| "images/2013-07-04_A-1_00014-00016_8_00009857.jpg"] | |
| # iface = gr.Interface(query_image, inputs=gr.inputs.Image(type="pil"), outputs=gr.outputs.Image(type="pil"), | |
| # examples=examples) | |
| # iface.launch() | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| # Traffic sign detection | |
| """ | |
| ) | |
| with gr.Row().style(equal_height=True): | |
| img1 = gr.Image(type="pil", label="Input image") | |
| with gr.Row(): | |
| process_button = gr.Button("Detect", visible=True) | |
| with gr.Row(): | |
| img2 = gr.Image(interactive=False, label="Output image with predicted pose") | |
| process_button.click(fn=query_image, inputs=[img1], outputs=[img2]) | |
| examples = gr.Examples(examples=examples, inputs=[img1]) | |
| demo.queue().launch(show_api=False) | |