import gradio as gr
import PIL.Image as Image

from ultralytics import ASSETS, YOLO

model_egg = YOLO("EPR_Detection/weights/egg_best.pt")
model_nest = YOLO("EPR_Detection/weights/nest_best.pt")

def predict_egg_image(img, conf_threshold, iou_threshold):
    """Predicts objects in an image using a YOLO model with adjustable confidence and IOU thresholds."""
    results = model_egg.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


def predict_nest_image(img, conf_threshold, iou_threshold):
    """Predicts objects in an image using a YOLO model with adjustable confidence and IOU thresholds."""
    results = model_nest.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_egg = gr.Interface(
    fn=predict_egg_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="EPR Egg Detection",
    description="Upload images for egg detection inference.",
    examples=[
        ["EPR_Detection/Examples/Egg/egg1.jpg", 0.25, 0.45],
        ["EPR_Detection/Examples/Egg/egg2.jpg", 0.25, 0.45],
        ["EPR_Detection/Examples/Egg/egg3.jpg", 0.25, 0.45],
        ["EPR_Detection/Examples/Egg/egg4.jpg", 0.25, 0.45],
        ["EPR_Detection/Examples/Egg/egg5.jpg", 0.25, 0.45]
    ],
)

iface_nest = gr.Interface(
    fn=predict_nest_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="EPR Nest Detection",
    description="Upload images for nest detection inference.",
    examples=[
        ["EPR_Detection/Examples/Nest/nest1.jpg", 0.15, 0.15],
        ["EPR_Detection/Examples/Nest/nest2.jpg", 0.15, 0.15],
        ["EPR_Detection/Examples/Nest/nest3.jpg", 0.15, 0.15],
        ["EPR_Detection/Examples/Nest/nest4.jpg", 0.15, 0.15],
        ["EPR_Detection/Examples/Nest/nest5.jpg", 0.15, 0.15]
    ],
)

iface = gr.TabbedInterface(
    [iface_egg, iface_nest],
    ["EPR Egg", "EPR Nest"]
)

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