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import utils
import gradio as gr
# constants
DEFAULT_MODEL = "yolov8l-world.pt"
VIDEO_EXAMPLES = [
['https://media.roboflow.com/supervision/video-examples/croissant-1280x720.mp4',
'croissant', 0.01, 0.2],
['https://media.roboflow.com/supervision/video-examples/suitcases-1280x720.mp4',
'suitcase', 0.1, 0.2],
['https://media.roboflow.com/supervision/video-examples/tokyo-walk-1280x720.mp4',
'woman walking', 0.1, 0.2],
['https://media.roboflow.com/supervision/video-examples/wooly-mammoth-1280x720.mp4',
'mammoth', 0.01, 0.2],
]
CACHE_EXAMPLES = False
# load the YOLO model
model = utils.yolo_model(DEFAULT_MODEL)
# CSS to hide the footer and reduce the height of the Gradio interface
css = "footer {display: none !important;} .gradio-container {min-height: 0px !important;}"
with gr.Blocks(css=css) as demo:
# title and description
gr.Markdown("# YOLO-World video processing")
gr.Markdown(
"Upload a video and click the button to process it with YOLO-World")
# define the structure of the interface
with gr.Row():
input_video = gr.Video(label="Input video")
output_video = gr.Video(label="Output video")
with gr.Row():
# prompt and button
prompt = gr.Textbox(
label='Categories',
placeholder='comma separated list of categories',
scale=5
)
button = gr.Button("Process video")
with gr.Row():
with gr.Column():
with gr.Row():
confidence = gr.Slider(
minimum=0, maximum=1, value=0.25, label="Confidence threshold", step=0.01)
with gr.Row():
iou = gr.Slider(minimum=0, maximum=1, value=0.7,
label="IoU threshold", step=0.01)
with gr.Column():
model_to_load = gr.Dropdown(["yolov8s-world.pt", "yolov8m-world.pt", "yolov8l-world.pt"],
label="Model", info="Select the model to use", value=DEFAULT_MODEL)
gr.Button("Upload model").click(model.load, inputs=[model_to_load])
# examples
with gr.Row():
gr.Examples(
examples=VIDEO_EXAMPLES,
inputs=[input_video, prompt, confidence, iou],
outputs=output_video,
fn=model.process,
cache_examples=CACHE_EXAMPLES,
)
# click event
button.click(model.process, inputs=[
input_video, prompt, confidence, iou], outputs=output_video)
gr.close_all()
demo.launch()
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