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import gradio as gr
import torch
from ultralyticsplus import YOLO, render_result
# Images
torch.hub.download_url_to_file('https://external-content.duckduckgo.com/iu/?u=https%3A%2F%2Ftexashafts.com%2Fwp-content%2Fuploads%2F2016%2F04%2Fconstruction-worker.jpg', 'one.jpg')
torch.hub.download_url_to_file(
'https://www.pearsonkoutcherlaw.com/wp-content/uploads/2020/06/Construction-Workers.jpg', 'two.jpg')
torch.hub.download_url_to_file(
'https://nssgroup.com/wp-content/uploads/2019/02/Building-maintenance-blog.jpg', 'three.jpg')
def yoloV8_func(image: gr.inputs.Image = None,
image_size: gr.inputs.Slider = 640,
conf_threshold: gr.inputs.Slider = 0.4,
iou_threshold: gr.inputs.Slider = 0.50):
"""_summary_
Args:
image (gr.inputs.Image, optional): _description_. Defaults to None.
image_size (gr.inputs.Slider, optional): _description_. Defaults to 640.
conf_threshold (gr.inputs.Slider, optional): _description_. Defaults to 0.4.
iou_threshold (gr.inputs.Slider, optional): _description_. Defaults to 0.50.
"""
model_path = "best.pt"
model = YOLO("foduucom/table-detection-and-extraction")
results = model.predict(image,
conf=conf_threshold,
iou=iou_threshold,
imgsz=image_size)
# observe results
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
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"),
]
outputs = gr.outputs.Image(type="filepath", label="Output Image")
title = "YOLOv8 101: Custome Object Detection on Construction Workers "
examples = [['one.jpg', 640, 0.5, 0.7],
['two.jpg', 800, 0.5, 0.6],
['three.jpg', 900, 0.5, 0.8]]
yolo_app = gr.Interface(
fn=yoloV8_func,
inputs=inputs,
outputs=outputs,
title=title,
examples=examples,
cache_examples=True,
#theme='huggingface',
)
yolo_app.launch(debug=True, enable_queue=True) |