import configparser
import cv2
import os
import time
from discord_webhook import DiscordWebhook, DiscordEmbed
import logging
from datetime import datetime
from pycoral.adapters.common import input_size
from pycoral.adapters.detect import get_objects
from pycoral.utils.dataset import read_label_file
from pycoral.utils.edgetpu import make_interpreter
from pycoral.utils.edgetpu import run_inference
 

def main():
    last_time = datetime.now()
    time.sleep(5)
    webhook = DiscordWebhook(url=config["DEFAULT"]["url"])
    labels=config["DEFAULT"]["default_labels"]
    model=config["DEFAULT"]["default_model"]
    threshold=float(config["DEFAULT"]["default_threshold"])
    top_k= int(config["DEFAULT"]["top_K"])
    grace_time= int(config["DEFAULT"]["grace_time"])
    stream=config["DEFAULT"]["default_stream"]
    dump_path=config["DEFAULT"]["dump_path"]
    logging.warning('Loading {} with {} labels.'.format(model, labels))
    interpreter = make_interpreter(model)
    interpreter.allocate_tensors()
    labels = read_label_file(labels)
    inference_size = input_size(interpreter)

    cap = cv2.VideoCapture(stream)

    while cap.isOpened():
        
        ret, frame = cap.read()
        if not ret:
            break 
        cv2_im = frame

        cv2_im_rgb = cv2.cvtColor(cv2_im, cv2.COLOR_BGR2RGB)
        cv2_im_rgb = cv2.resize(cv2_im_rgb, inference_size)
        run_inference(interpreter, cv2_im_rgb.tobytes())
        objs = get_objects(interpreter,threshold)[:top_k]
        cv2_im,alarm,message = detect_and_alarm(cv2_im, inference_size, objs, labels,threshold)
        #print(alarm,message)
        if alarm and is_time(last_time,grace_time):
            last_time=datetime.now()
            logging.warning("people alarm",last_time)
            #im_resize = cv2.resize(cv2_im, (640, 480))
            is_success, im_buf_arr = cv2.imencode(".jpg", cv2_im)
            byte_im = im_buf_arr.tobytes()
            webhook.add_file(file=byte_im,filename='capture.png')
            embed = DiscordEmbed(title='Detected', description=message, color='ff2345')
            embed.set_image(url='attachment://capture.png')
            webhook.add_embed(embed)
            response = webhook.execute(remove_embeds=True)
            logging.debug(response)
            if config["DEFAULT"]["DUMP_VIDEO"]=="True":
                os.system(f"ffmpeg -i {stream} -acodec copy -vcodec copy -t {grace_time} {dump_path}record_{last_time.strftime('%d-%m-%Y_%H-%M-%S')}.mp4 ")
        if config["DEFAULT"]["CV_DEBUG"]=="True":
            cv2.imshow('frame', cv2_im)
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break

    cap.release()
    cv2.destroyAllWindows()


def detect_and_alarm (cv2_im, inference_size, objs, labels,threshold):
    height, width, channels = cv2_im.shape
    scale_x, scale_y = width / inference_size[0], height / inference_size[1]
    for obj in objs:
        if obj.id == 0  and obj.score>threshold*1.09:  
            bbox = obj.bbox.scale(scale_x, scale_y)
            x0, y0 = int(bbox.xmin), int(bbox.ymin)
            x1, y1 = int(bbox.xmax), int(bbox.ymax)
            percent = int(100 * obj.score)
            label = '{}% {}'.format(percent, labels.get(obj.id, obj.id))
            cv2_im = cv2.rectangle(cv2_im, (x0, y0), (x1, y1), (0, 255, 0), 2)
            cv2_im = cv2.putText(cv2_im, label, (x0, y0+30),
                                 cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 0, 0), 2)
            cv2_im = cv2.putText(cv2_im, "ALARM !!!!", (10,30),
                                 cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255), 2)
            return cv2_im,True,f'ALARM ! PERSON detected {round(obj.score,1)*100}'
    return cv2_im,False,"OKAY"

def is_time(last_time,threshold):
    delta=int((datetime.now()-last_time).total_seconds())
    logging.debug(delta,last_time,threshold,delta >= threshold)
    return delta >= threshold


if __name__ == '__main__':
    config = configparser.ConfigParser()  
    configFilePath = '/home/pi/picoral_cctv/cctv.ini'
    config.read(configFilePath)
    main()