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import gradio as gr
from ultralytics import YOLO
import supervision as sv
import os
os.system("wget https://media.roboflow.com/notebooks/examples/dog.jpeg")
os.system("wget https://media.roboflow.com/notebooks/examples/dog-2.jpeg")
def detect(image, weights, slider_val):
model = YOLO(weights + '.pt')
result = model(image, verbose=False)[0]
detections = sv.Detections.from_ultralytics(result)
box_annotator = sv.BoxAnnotator()
annotated_image = box_annotator.annotate(
image.copy(), detections=detections)
return annotated_image
inputs_thresh = [
gr.inputs.Image(type="numpy", label="Input Image"),
gr.inputs.Radio(label="Detection Methods",
choices=[
"yolov5s", "yolov8s"
]),
gr.components.Slider(label="Class Probability Value",
value=10, minimum=1, maximum=100, step=1),
]
outputs_thresh = [
gr.outputs.Image(type="numpy", label="Output Image")
]
detect_tab = gr.Interface(
detect,
inputs=inputs_thresh,
outputs=outputs_thresh,
title="supervision",
examples=[["dog.jpeg", "yolov5s"], ["dog-2.jpeg", "yolov8s"]],
description="Gradio based demo for <a href='https://github.com/roboflow/supervision' style='text-decoration: underline' target='_blank'>roboflow/supervision</a>, We write your reusable computer vision tools."
)
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