Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| # import torch | |
| from ultralyticsplus import YOLO, render_result | |
| classes: ['car', 'bike', 'person', 'car_car_accident', 'car_bike_accident', 'car_person_accident', 'bike_bike_accidnet', 'bike_person_accident', 'car_object_accident', 'bike_object_accident'] | |
| def yolov8_func(image): | |
| #image_size: gr.inputs.Slider = 640, | |
| #conf_threshold: gr.inputs.Slider = 0.4, | |
| #iou_threshold: gr.inputs.Slider = 0.50): | |
| model_path = "best.pt" | |
| model = YOLO(model_path) | |
| results = model.predict(image, | |
| conf = 0.4, | |
| iou = 0.6, | |
| imgsz = 640) | |
| box = results[0].boxes | |
| print("Object type: ", box.cls) | |
| # print("Coordinates: ", box.xyxy) | |
| # print("Probability: ", box.conf) | |
| render = render_result(model=model, image=image, result=results[0]) | |
| return render, box.cls | |
| # inputs = [ | |
| # gr.inputs.Image(type="filepath", label="Input Image"), | |
| # gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"), | |
| # gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"), | |
| # gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="Iou Threshold") | |
| # ] | |
| # gr.HTML | |
| # outputs = gr.outputs.Image(type="filepath", label="Output Image") | |
| # yolo_app = gr.Interface( | |
| # fn=yolov8_func, | |
| # inputs=inputs, | |
| # outputs=outputs, | |
| # title="Accident detector", | |
| # ) | |
| # yolo_app.launch(debug=True, enable_queue=True) | |
| with gr.Blocks(title="YOLOS Object Detection - ClassCat", css=".gradio-container {background:lightyellow;}") as demo: | |
| gr.HTML('<h1>Yolo Object Detection</h1>') | |
| #gr.HTML("<h4>supported objects are [aeroplane,bicycle,bird,boat,bottle,bus,car,cat,chair,cow,diningtable,dog,horse,motorbike,person,pottedplant,sheep,sofa,train,tvmonitor]</h4>") | |
| gr.HTML("<br>") | |
| with gr.Row(): | |
| input_image = gr.Image(label="Input image", type="pil") | |
| output_image = gr.Image(label="Output image", type="pil") | |
| output_label = gr.Text(label="output label") | |
| gr.HTML("<br>") | |
| #gr.HTML("<h4>object centre detection threshold means the object centre will be considered a new object if it's value is above threshold</h4>") | |
| #gr.HTML("<p>less means more objects</p>") | |
| #gr.HTML("<h4>bounding box threshold is IOU value threshold. If intersection/union area of two bounding boxes are greater than threshold value the one box will be suppressed</h4>") | |
| #gr.HTML("<p>more means more bounding boxes<p>") | |
| #gr.HTML("<br>") | |
| #obj_threshold = gr.Slider(0, 1.0, value=0.2, label=' object centre detection threshold') | |
| #gr.HTML("<br>") | |
| #bb_threshold = gr.Slider(0, 1.0, value=0.3, label=' bounding box draw threshold') | |
| #gr.HTML("<br>") | |
| send_btn = gr.Button("Detect") | |
| gr.HTML("<br>") | |
| #gr.Examples(['./samples/out_1.jpg'], inputs=input_image) | |
| send_btn.click(fn=yolov8_func, inputs=[input_image], outputs=[output_image, output_label]) | |
| demo.launch(debug=True) | |