import os


def render(kernel, epochs, train_datasets, valid_datasets,
           val_images, accuracy, precision, recall):
    return f"""
# Model Info
* Kernel: {kernel}
* Epochs: {epochs}
* TrainSet: {train_datasets}
* ValidSet: {valid_datasets}
# Metrics
* Accuracy: {accuracy}
* Precision: {precision}
* Recall: {recall}
# Confusion Matrix
![confusion_matrix](./confusion_matrix.png)
# Valid Image Example
{render_list(val_images)}
""".strip()


def render_list(lst):
    return "".join(render_list_iter(lst))


def render_list_iter(lst):
    for item in lst:
        yield f"""{render_item(item)}\n"""


def render_item(item: tuple[str, str]):
    original, pred = item
    return f"""
### Original Image
![original_image]({original})
### Predicted Image
![predicted_image]({pred})
""".strip()


def main(val_images: list[tuple[str, str]]):

    return render(kernel='yolov5s', epochs=100, train_datasets='coco', valid_datasets='coco',
                  val_images=val_images,
                  accuracy=0.9, precision=0.8, recall=0.7)


if __name__ == '__main__':
    out = 'datasets/coco8/images/report/report.md'
    imgs = list(map(lambda x: (f"../val/{x}", f"../val/{x}"), os.listdir('datasets/coco8/images/val')))

    with open(out, 'w') as f:
        f.write(main(val_images=imgs))