app/utils.py

########################################################################################################################
# ------------------------------------------- of AUTHOR: Omm AKA Antonio Colapso---------------------------------------#
########################################################################################################################
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="")
# Mapping integers back to original characters
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(frame)
        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]
    
    # Define the base directories
    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'))

    # Construct the full paths
    video_path = os.path.join(data_dir, f'{file_name}.mpg')
    alignment_path = os.path.join(alignment_dir, f'{file_name}.align')

    # Check if the files exist
    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

# def load_data(path: str): 
#     path = bytes.decode(path.numpy())
#     file_name = path.split('/')[-1].split('.')[0]
#     # File name splitting for windows
#     file_name = path.split('\\')[-1].split('.')[0]
#     video_path = os.path.join('..','data','s1',f'{file_name}.mpg')
#     alignment_path = os.path.join('..','data','alignments','s1',f'{file_name}.align')
#     frames = load_video(video_path) 
#     alignments = load_alignments(alignment_path)
    
#     return frames, alignments