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Running
File size: 2,280 Bytes
e6a096b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | 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
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