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Update preprocess_lrs2lrs3.py #53

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161 changes: 133 additions & 28 deletions preparation/preprocess_lrs2lrs3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,33 @@
default=0,
help="Index to identify separate jobs (useful for parallel processing).",
)
# args = parser.parse_args()

# seg_duration = args.seg_duration
# dataset = args.dataset
# text_transform = TextTransform()

# # Load Data
# args.data_dir = os.path.normpath(args.data_dir)
# if args.gpu_type != "cuda" or "mps":
# raise ValueError("Invalid GPU type. Valid values for gpu_type are \"cuda\" and \"mps\". ")
# vid_dataloader = AVSRDataLoader(
# modality="video", detector=args.detector, convert_gray=False, gpu_type=args.gpu_type
# )
# aud_dataloader = AVSRDataLoader(modality="audio")

# seg_vid_len = seg_duration * 25
# seg_aud_len = seg_duration * 16000

# # Label filename
# label_filename = os.path.join(
# args.root_dir,
# "labels",
# f"{dataset}_{args.subset}_transcript_lengths_seg{seg_duration}s.csv"
# if args.groups <= 1
# else f"{dataset}_{args.subset}_transcript_lengths_seg{seg_duration}s.{args.groups}.{args.job_index}.csv",
# )
#my code----------------------------------------------------
args = parser.parse_args()

seg_duration = args.seg_duration
Expand All @@ -91,10 +118,14 @@

# Load Data
args.data_dir = os.path.normpath(args.data_dir)
if args.gpu_type != "cuda" or "mps":
raise ValueError("Invalid GPU type. Valid values for gpu_type are \"cuda\" and \"mps\". ")

# GPU type validation (sanitized)
gpu_type = args.gpu_type.strip().lower()
if gpu_type not in ["cuda", "mps"]:
raise ValueError('Invalid GPU type. Valid values for gpu_type are "cuda" and "mps".')

vid_dataloader = AVSRDataLoader(
modality="video", detector=args.detector, convert_gray=False, gpu_type=args.gpu_type
modality="video", detector=args.detector, convert_gray=False, gpu_type=gpu_type
)
aud_dataloader = AVSRDataLoader(modality="audio")

Expand All @@ -109,6 +140,8 @@
if args.groups <= 1
else f"{dataset}_{args.subset}_transcript_lengths_seg{seg_duration}s.{args.groups}.{args.job_index}.csv",
)
#--------------------------------------

os.makedirs(os.path.dirname(label_filename), exist_ok=True)
print(f"Directory {os.path.dirname(label_filename)} created")

Expand Down Expand Up @@ -137,36 +170,108 @@
filenames.sort()
else:
raise NotImplementedError
# elif dataset == "lrs2":
# if args.subset in ["val", "test"]:
# filenames = [
# os.path.join(args.data_dir, "main", _.split()[0] + ".mp4")
# for _ in open(
# os.path.join(os.path.dirname(args.data_dir), args.subset) + ".txt"
# )
# .read()
# .splitlines()
# ]
# elif args.subset == "train":
# filenames = [
# os.path.join(args.data_dir, "main", _.split()[0] + ".mp4")
# for _ in open(
# os.path.join(os.path.dirname(args.data_dir), args.subset) + ".txt"
# )
# .read()
# .splitlines()
# ]
# pretrain_filenames = [
# os.path.join(args.data_dir, "pretrain", _.split()[0] + ".mp4")
# for _ in open(os.path.join(os.path.dirname(args.data_dir), "pretrain.txt"))
# .read()
# .splitlines()
# ]
# filenames.extend(pretrain_filenames)
# filenames.sort()
# else:
# raise NotImplementedError
#my condition -----------------------------------------
elif dataset == "lrs2":
if args.subset in ["val", "test"]:
filenames = [
os.path.join(args.data_dir, "main", _.split()[0] + ".mp4")
for _ in open(
os.path.join(os.path.dirname(args.data_dir), args.subset) + ".txt"
)
.read()
.splitlines()
]
# Build the path to the subset text file
subset_file = os.path.join(os.path.dirname(args.data_dir), f"{args.subset}.txt")

filenames = []
try:
with open(subset_file, 'r') as f:
for line in f:
line = line.strip()
if not line: # Skip empty lines
continue
parts = line.split()
if parts: # Only proceed if we have content
video_id = parts[0]
mp4_path = os.path.join(args.data_dir, "main", f"{video_id}.mp4")
if os.path.exists(mp4_path):
filenames.append(mp4_path)
else:
print(f"Warning: Video file not found - {mp4_path}")
except FileNotFoundError:
print(f"Error: Could not find subset file at {subset_file}")
exit(1)

elif args.subset == "train":
filenames = [
os.path.join(args.data_dir, "main", _.split()[0] + ".mp4")
for _ in open(
os.path.join(os.path.dirname(args.data_dir), args.subset) + ".txt"
)
.read()
.splitlines()
]
pretrain_filenames = [
os.path.join(args.data_dir, "pretrain", _.split()[0] + ".mp4")
for _ in open(os.path.join(os.path.dirname(args.data_dir), "pretrain.txt"))
.read()
.splitlines()
]
# Process main training files
train_file = os.path.join(os.path.dirname(args.data_dir), "train.txt")
filenames = []

try:
with open(train_file, 'r') as f:
for line in f:
line = line.strip()
if not line:
continue
parts = line.split()
if parts:
video_id = parts[0]
mp4_path = os.path.join(args.data_dir, "main", f"{video_id}.mp4")
if os.path.exists(mp4_path):
filenames.append(mp4_path)
else:
print(f"Warning: Training video not found - {mp4_path}")
except FileNotFoundError:
print(f"Error: Could not find training file at {train_file}")
exit(1)

# Process pretrain files
pretrain_file = os.path.join(os.path.dirname(args.data_dir), "pretrain.txt")
pretrain_filenames = []

try:
with open(pretrain_file, 'r') as f:
for line in f:
line = line.strip()
if not line:
continue
parts = line.split()
if parts:
video_id = parts[0]
mp4_path = os.path.join(args.data_dir, "pretrain", f"{video_id}.mp4")
if os.path.exists(mp4_path):
pretrain_filenames.append(mp4_path)
else:
print(f"Warning: Pretrain video not found - {mp4_path}")
except FileNotFoundError:
print(f"Error: Could not find pretrain file at {pretrain_file}")
exit(1)

filenames.extend(pretrain_filenames)
filenames.sort()
else:
raise NotImplementedError

#--------------------------------------------
unit = math.ceil(len(filenames) * 1.0 / args.groups)
filenames = filenames[args.job_index * unit : (args.job_index + 1) * unit]

Expand Down