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import gradio as gr | |
import spaces | |
from huggingface_hub import hf_hub_download | |
def yolov9_inference(img_path, conf_threshold, iou_threshold): | |
""" | |
Load a YOLOv9 model, configure it, perform inference on an image, and optionally adjust | |
the input size and apply test time augmentation. | |
:param model_path: Path to the YOLOv9 model file. | |
:param conf_threshold: Confidence threshold for NMS. | |
:param iou_threshold: IoU threshold for NMS. | |
:param img_path: Path to the image file. | |
:param size: Optional, input size for inference. | |
:return: A tuple containing the detections (boxes, scores, categories) and the results object for further actions like displaying. | |
""" | |
# Import YOLOv9 | |
import yolov9 | |
# Load the model | |
model_path = "yolov9-plant.pt" | |
model = yolov9.load(model_path, device="cuda:0") | |
# Set model parameters | |
model.conf = conf_threshold | |
model.iou = iou_threshold | |
# Perform inference | |
results = model(img_path, size=640) | |
# Optionally, show detection bounding boxes on image | |
output = results.render() | |
return output[0] | |
def app(): | |
with gr.Blocks(): | |
with gr.Row(): | |
with gr.Column(): | |
img_path = gr.Image(type="filepath", label="Image") | |
conf_threshold = gr.Slider( | |
label="Confidence Threshold", | |
minimum=0.1, | |
maximum=1.0, | |
step=0.1, | |
value=0.4, | |
) | |
iou_threshold = gr.Slider( | |
label="IoU Threshold", | |
minimum=0.1, | |
maximum=1.0, | |
step=0.1, | |
value=0.5, | |
) | |
yolov9_infer = gr.Button(value="Inference") | |
with gr.Column(): | |
output_numpy = gr.Image(type="numpy",label="Output") | |
yolov9_infer.click( | |
fn=yolov9_inference, | |
inputs=[ | |
img_path, | |
conf_threshold, | |
iou_threshold, | |
], | |
outputs=[output_numpy], | |
) | |
gr.Examples( | |
examples=[ | |
[ | |
"data/apple_d1.jpg", | |
0.4, | |
0.5, | |
], | |
], | |
fn=yolov9_inference, | |
inputs=[ | |
img_path, | |
model_path, | |
image_size, | |
conf_threshold, | |
iou_threshold, | |
], | |
outputs=[output_numpy], | |
cache_examples=True, | |
) | |
gradio_app = gr.Blocks() | |
with gradio_app: | |
gr.HTML( | |
""" | |
<h1 style='text-align: center'> | |
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information | |
</h1> | |
""") | |
with gr.Row(): | |
with gr.Column(): | |
app() | |
gradio_app.launch(debug=True) |