from __future__ import annotations
from typing import List
import cv2
import os
import tensorflow as tf

# Disable all GPUS
tf.config.set_visible_devices([], 'GPU')

vocab = [x for x in "abcdefghijklmnopqrstuvwxyz'?!123456789 "]
char_to_num = tf.keras.layers.StringLookup(vocabulary=vocab, oov_token="")
num_to_char = tf.keras.layers.StringLookup(
    vocabulary=char_to_num.get_vocabulary(), oov_token="", invert=True
)

def load_video(path: str) -> List[float]:
    cap = cv2.VideoCapture(path)
    frames = []
    for _ in range(int(cap.get(cv2.CAP_PROP_FRAME_COUNT))): 
        ret, frame = cap.read()
        if not ret or frame is None:
            break
        frame = tf.image.rgb_to_grayscale(tf.cast(frame, tf.float32))
        frames.append(frame[190:236, 80:220, :])
    cap.release()
    if not frames:
        raise ValueError(f"No frames were read from video: {path}")
    mean = tf.math.reduce_mean(frames)
    std = tf.math.reduce_std(tf.cast(frames, tf.float32))
    return tf.cast((frames - mean), tf.float32) / std

def load_alignments(path: str) -> List[str]:
    with open(path, 'r') as f:
        lines = f.readlines()
    tokens = []
    for line in lines:
        line = line.split()
        if len(line) < 3:
            continue
        if line[2] != 'sil':
            tokens = [*tokens, ' ', line[2]]
    return char_to_num(
        tf.reshape(tf.strings.unicode_split(tokens, input_encoding='UTF-8'), (-1))
    )[1:]

def load_data(path: str):
    path = bytes.decode(path.numpy())
    file_name = os.path.splitext(os.path.basename(path))[0]

    BASE_DIR = os.path.dirname(os.path.abspath(__file__))
    data_dir = os.path.abspath(os.path.join(BASE_DIR, 'data', 's1'))
    alignment_dir = os.path.abspath(os.path.join(BASE_DIR, 'data', 'alignments', 's1'))

    video_path = os.path.join(data_dir, f'{file_name}.mpg')
    alignment_path = os.path.join(alignment_dir, f'{file_name}.align')

    if not os.path.exists(video_path):
        raise FileNotFoundError(f"Video file {video_path} does not exist.")
    if not os.path.exists(alignment_path):
        raise FileNotFoundError(f"Alignment file {alignment_path} does not exist.")

    frames = load_video(video_path)
    alignments = load_alignments(alignment_path)
    return frames, alignments