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from ultralytics import YOLO
import gradio as gr
import numpy as np
from PIL import Image
# -------------------------
# Load ONLY your trained model
# -------------------------
model = YOLO("mules_vs_whitetails.pt")
# -------------------------
# Inference function
# -------------------------
def predict(image):
# Ensure RGB numpy array
if isinstance(image, Image.Image):
image = np.array(image.convert("RGB"))
# Run inference
results = model.predict(
source=image,
conf=0.25,
device="cpu", # change to "cuda" if GPU is available
verbose=False
)
# Take first result
r = results[0]
# Draw detections (BGR → RGB)
im_bgr = r.plot()
im_rgb = im_bgr[:, :, ::-1]
return im_rgb
# -------------------------
# Gradio UI
# -------------------------
app = gr.Interface(
fn=predict,
inputs=gr.Image(type="numpy", label="Upload Image"),
outputs=gr.Image(type="numpy", label="Detection Result"),
title="Deer Detection AI – Mule Deer vs Whitetail",
description="Custom YOLO model: mules_vs_whitetails.pt"
)
# -------------------------
# Launch
# -------------------------
if __name__ == "__main__":
app.launch()
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