import gradio as gr
import torch
import yolov7


# Images
#torch.hub.download_url_to_file('https://raw.githubusercontent.com/nihalbaig0/BD-Vehicle-Detection/main/images/bondor_to_kodomtoli.jpg', 'bondor_to_kodomtoli.jpg')
#torch.hub.download_url_to_file('https://raw.githubusercontent.com/nihalbaig0/BD-Vehicle-Detection/main/images/lamabazar_to_versitygate.jpg', 'lamabazar_to_versitygate.jpg')
    
def yolov7_inference(
    image: gr.inputs.Image = None,
    model_path: gr.inputs.Dropdown = None,
    image_size: gr.inputs.Slider = 640,
    conf_threshold: gr.inputs.Slider = 0.25,
    iou_threshold: gr.inputs.Slider = 0.45,
):
    """
    YOLOv7 inference function
    Args:
        image: Input image
        model_path: Path to the model
        image_size: Image size
        conf_threshold: Confidence threshold
        iou_threshold: IOU threshold
    Returns:
        Rendered image
    """

    model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
    model.conf = conf_threshold
    model.iou = iou_threshold
    results = model([image], size=image_size)
    return results.render()[0]
        

inputs = [
    gr.inputs.Image(type="pil", label="Input Image"),
    gr.inputs.Dropdown(
        choices=[
            "nihalbaig/yolov7",
            
        ],
        default="nihalbaig0/yolov7",
        label="Model",
    ),
    gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),
    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),
]

outputs = gr.outputs.Image(type="filepath", label="Output Image")
title = "Project-350: BD Vehicle Detection for Autonomous Vehicle"

#examples = [['bondor_to_kodomtoli.jpg', 'nihalbaig0/yolov7', 640, 0.25, 0.45], ['lamabazar_to_versitygate.jpg', 'nihalbaig0/yolov7', 640, 0.25, 0.45]]
demo_app = gr.Interface(
    fn=yolov7_inference,
    inputs=inputs,
    outputs=outputs,
    title=title,
    #examples=examples,
    cache_examples=True,
    theme='darkhuggingface',
)
demo_app.launch(debug=True, enable_queue=True)