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# Visualise detections on input image
cols = st.columns(len(pipeline_ids))
captions = ["YOLOv4", "YOLOv7"]
for col, (resp, boxes_ltwh, categories, scores), cap in zip(cols, pipeline_results, captions):
    if resp.status_code == 200:
        # Show image overlaid with detection results
        img_draw = draw_detection(img, boxes_ltwh, categories, scores)
        col.image(img_draw, use_column_width=True, caption=cap)
    else:
        col.error("{} inference error".format(cap))

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# Trigger VDP pipelines
pipeline_ids = [opt.yolov4, opt.yolov7]
pipeline_results = []
for pipeline_id in pipeline_ids:
    resp = trigger_detection_pipeline(pipeline_backend_base_url, pipeline_id, image_url)
    boxes_ltwh, categories, scores = parse_detection_response(resp)
    pipeline_results.append((resp, boxes_ltwh, categories, scores))

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def parse_detection_response(resp: requests.Response):
    r""" Parse a detection response
    
    Args:
        resp (`requests.Response`): response for standardised object detection task
    
    Returns: parsed outputs, a tuple of 
        List[Tuple[float]]: a list of detected bounding boxes in the format of (top, left, width, height)
        List[str]: a list of category labels, each of which corresponds to a detected bounding box. The length of this list must be the same as the detected bounding boxes.
        List[float]]: a list of scores, each of which corresponds to a detected bounding box. The length of this list must be the same as the detected bounding boxes.

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def trigger_detection_pipeline(pipeline_backend_base_url: str, pipeline_id: str, image_url: str) -> requests.Response:
    r""" Trigger a pipeline composed with a detection model instance using remote image URL
    Args:
        pipeline_backend_base_url (string): VDP pipeline backend base URL
        pipeline_id (string): pipeline ID
        image_url (string): remote image URL, e.g., `https://artifacts.instill.tech/dog.jpg`
    Returns: requests.Response
        pipeline trigger result
    """
    body = {

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# Use image remote URL to fetch an image as input
image_url = st.text_input(
    label="Feed me with an image URL and press ENTER", value="https://artifacts.instill.tech/dog.jpg")