Spaces:
Runtime error
Runtime error
File size: 2,025 Bytes
3cbf1d1 8981abe 3cbf1d1 8981abe 3cbf1d1 c49c9b0 8981abe 3cbf1d1 8981abe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
import gradio as gr
import torch
import yolov7
# Images
torch.hub.download_url_to_file('https://github.com/Michael-OvO/Burn-Detection-Classification/blob/main/inference/images/1st_degree_1.jpg', '1st_degree_1.jpg')
torch.hub.download_url_to_file('https://github.com/Michael-OvO/Burn-Detection-Classification/blob/main/inference/images/3rd_degree_1.jpg', '3rd_degree_1.jpg')
def yolov7_inference(
image: gr.inputs.Image = None,
model_path: gr.inputs.Dropdown = None,
image_size: gr.inputs.Slider = 640,
conf_threshold: gr.inputs.Slider = 0.25,
iou_threshold: gr.inputs.Slider = 0.45,
):
"""
YOLOv7 inference function
Args:
image: Input image
model_path: Path to the model
image_size: Image size
conf_threshold: Confidence threshold
iou_threshold: IOU threshold
Returns:
Rendered image
"""
model = torch.hub.load('kadirnar/yolov7-v0.1', 'custom', path='skin_burn.pt', source='local', device="cpu")
model.conf = conf_threshold
model.iou = iou_threshold
results = model([image], size=image_size)
return results.render()[0]
inputs = [
gr.inputs.Image(type="pil", label="Input Image"),
gr.inputs.Dropdown(
choices=[
"skin_burn",
"kadirnar/yolov7-v0.1",
],
default="skin_burn",
label="Model",
),
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 = "Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors"
demo_app = gr.Interface(
fn=yolov7_inference,
inputs=inputs,
outputs=outputs,
title=title,
theme='huggingface',
)
demo_app.launch(debug=True, enable_queue=True)
|