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import gradio as gr | |
import PIL.Image as Image | |
from ultralytics import ASSETS, YOLO | |
model = YOLO("https://huggingface.co/spaces/gpbhupinder/test/blob/main/model_-%2023%20june%202024%2019_22.pt") | |
def predict_image(img): | |
"""Predicts objects in an image using a YOLOv8 model.""" | |
results = model.predict( | |
source=img, | |
show_labels=True, | |
show_conf=True, | |
imgsz=640, | |
) | |
for r in results: | |
im_array = r.plot() | |
im = Image.fromarray(im_array[..., ::-1]) | |
return im | |
iface = gr.Interface( | |
fn=predict_image, | |
inputs=[ | |
gr.Image(type="pil", label="Upload Image"), | |
# gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"), | |
# gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold"), | |
], | |
outputs=gr.Image(type="pil", label="Result"), | |
title="GP Wolf Classifier", | |
description="Upload images for inference.", | |
examples=[ | |
["gp.jpg"], | |
["wolf.jpg"], | |
], | |
) | |
if __name__ == "__main__": | |
iface.launch() |