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import subprocess
# install ultralytics
subprocess.check_call(["pip", "install", "ultralytics"])
from ultralytics import YOLO
from PIL import Image
import gradio as gr
from huggingface_hub import snapshot_download
import os
model_path = "/Users/markk/Downloads/best_int8_openvino_model"
def load_model(repo_id):
download_dir = snapshot_download(repo_id)
print(download_dir)
path = os.path.join(download_dir, "best_int8_openvino_model")
print(path)
detection_model = YOLO(path, task='detect')
return detection_model
def predict(pilimg):
source = pilimg
# x = np.asarray(pilimg)
# print(x.shape)
result = detection_model.predict(source, conf=0.5, iou=0.6)
img_bgr = result[0].plot()
out_pilimg = Image.fromarray(img_bgr[..., ::-1]) # RGB-order PIL image
return out_pilimg
REPO_ID = "khengkok/balloon_yolov8"
detection_model = load_model(REPO_ID)
gr.Interface(fn=predict,
inputs=gr.Image(type="pil"),
outputs=gr.Image(type="pil")
).launch(share=True)
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