import cv2
import gradio as gr
from z_app_factory import get_app


def inference(image):
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    annotated_image = image.copy()
    lst2d_res = get_app(image)
    thickness = 3
    lineType = 8
    font = cv2.FONT_HERSHEY_SIMPLEX

    for face in lst2d_res:
        bbox = [int(i) for i in face["bbox"]]
        score = face['score']
        point_color = (0, int(255 * score), 0) # BGR
        x1, y1 = bbox[:2]
        x2, y2 = bbox[2:]
        cv2.putText(annotated_image, str(score)[:4], (x1, y1 - 10), font, 0.8, (0, 255, 0), 2)
        cv2.line(annotated_image, (x1, y1), (x2, y1), point_color, thickness, lineType)
        cv2.line(annotated_image, (x2, y1), (x2, y2), point_color, thickness, lineType)
        cv2.line(annotated_image, (x1, y1), (x1, y2), point_color, thickness, lineType)
        cv2.line(annotated_image, (x1, y2), (x2, y2), point_color, thickness, lineType)

        for kp in face["kps"]:
            x, y = [int(i) for i in kp]
            cv2.circle(annotated_image, (x, y), 2, (2, 30, 200), 2)

    annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_RGB2BGR)
    return annotated_image



title = "Detect Face"
description = "demo for Detect Face. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
article = "<p style='text-align: center'><a href='https://www.yuque.com/itmorn/ability/detect_face' target='_blank'>Project Documents</a> | <a href='https://www.bilibili.com/video/BV1cg411v7CR' target='_blank'>Video Demo</a></p>"

gr.Interface(
    inference,
    [gr.inputs.Image(label="Input")],
    gr.outputs.Image(type="pil", label="Output"),
    title=title,
    description=description,
    article=article,
    examples=[
              ["imgs/face1.jpg"],
              ["imgs/face2.jpg"],
              ["imgs/11.jpg"]
    ]).launch(debug=True)