import PIL.Image as Image
import gradio as gr
from ultralytics import ASSETS, YOLO

model = YOLO("/home/jad-tounsi/Desktop/YAZ+/Yield/model_eval/weights/best.pt")


def predict_image(img, conf_threshold, iou_threshold):
    results = model.predict(
        source=img,
        conf=conf_threshold,
        iou=iou_threshold,
        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="My Yield | 🌱",
    description="Estimate the amount of plants per year",
    examples=[
        [ASSETS / "/home/jad-tounsi/Desktop/YAZ+/YAZ+ GPT/pages/asssets/test.jpg", 0.25, 0.45],
        [ASSETS / "/home/jad-tounsi/Desktop/YAZ+/YAZ+ GPT/pages/asssets/test2.jpg", 0.25, 0.45],
        [ASSETS / "/home/jad-tounsi/Desktop/YAZ+/YAZ+ GPT/pages/asssets/test3.jpg", 0.25, 0.45]
    ]
)

if __name__ == '__main__':
    iface.launch()