import cv2
import streamlit as st
import tempfile
from ffmpeg import FFmpeg

try:
    face_cascade = cv2.CascadeClassifier('XML/faces.xml')
except Exception:
    st.write("Error loading cascade classifiers")

def censor_face(filePath):
    
    #output_file = 'Output/censored_' + str(filePath.name) + '.mp4'
    
    video=cv2.VideoCapture(filePath.name)
    success, frame = video.read()
    
    height = frame.shape[0]
    width = frame.shape[1]

    #st.write(height, width)

    #gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    #st.write("Frame: " + str(frame))

    tfile2 = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
    #tfile2.write("Censored.mp4")
    
    output=cv2.VideoWriter(tfile2.name, cv2.VideoWriter_fourcc(*'mp4v2'), 30, (width, height))
    
    while success:
        faces = face_cascade.detectMultiScale(frame, 1.1, 4)
        for (x,y, w, h) in faces: #multiple faces in a video
            frame[y:y+h, x:x+w] = cv2.blur(frame[y:y+h, x:x+w], (50, 50))
            #st.write("frame")
        output.write(frame)
        success, frame = video.read()    
    
    
    #st.write(tfile2.name)
    #st.write(tfile2)

    ffmpeg = (
        FFmpeg()
        .option("y")
        .input(tfile2.name)
        .output(
            tfile2.name,
            {"codec:v": "libx264"},
            vf="scale=1280:-1",
            preset="veryslow",
            crf=24,
        )
    )

    ffmpeg.execute()
    
    result_video = open(tfile2.name, "rb")
    vid_bytes = result_video.read()
    #with open(tfile2.name, "rb") as file:
    #    btn = st.download_button(
    #            label="Download video",
    #            data=file,
    #            file_name=tfile2.name,
    #            mime="video/mp4"
    #          )

    #video_file = open(tfile2.name, 'rb')
    #video_bytes = video_file.read()
    st.video(vid_bytes)
    output.release()    
    video.release()
    return tfile2