File size: 6,077 Bytes
944cdc2 | 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 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 | import os
import json
from lzstring import LZString
from pycocotools import mask as mask_utils
import numpy as np
from PIL import Image
from decord import VideoReader
from decord import cpu
import argparse
import cv2
from time import time
def save_frames(frames, frame_idxes, output_folder, is_aria=False):
# resize and save frames
scale = 4
if is_aria:
scale = 2
for img, fidx in zip(frames, frame_idxes):
H, W, C = img.shape
if H < 1408:
break
img2 = cv2.resize(img, (W//scale, H//scale))
cv2.imwrite(os.path.join(output_folder, f'{fidx}.jpg'), img2)
def processVideo(takepath, take_name, ego_cam, exo_cams, outputpath, take_id):
if not os.path.exists(f"{takepath}/{take_name}/frame_aligned_videos/{ego_cam}.mp4"):
return -1
print("take_name:", take_name) # debug
# Subsample the ego video
vr = VideoReader(
f"{takepath}/{take_name}/frame_aligned_videos/{ego_cam}.mp4", ctx=cpu(0)
)
len_video = len(vr)
# subsampling at 1fps -- none of the videos are annotated at more than 1 fps
# subsample_idx = np.arange(0, len_video, 1) # debug
subsample_idx = np.arange(1020, 1621, 1) # debug
if not os.path.exists(f"{outputpath}/{take_id}/{ego_cam}"):
os.makedirs(f"{outputpath}/{take_id}/{ego_cam}")
frames = vr.get_batch(subsample_idx).asnumpy()[...,::-1]
save_frames(frames=frames, frame_idxes=subsample_idx, output_folder=f"{outputpath}/{take_id}/{ego_cam}", is_aria=True)
# Subsample the exo videos
for exo_cam in exo_cams:
if not os.path.isfile(f"{outputpath}/{take_id}/{exo_cam}.mp4"):
try:
vr = VideoReader(
f"{takepath}/{take_name}/frame_aligned_videos/{exo_cam}.mp4", ctx=cpu(0)
)
except:
print(f"{exo_cam} not available")
continue
os.makedirs(f"{outputpath}/{take_id}/{exo_cam}")
frames = vr.get_batch(subsample_idx).asnumpy()[...,::-1]
save_frames(frames=frames, frame_idxes=subsample_idx, output_folder=f"{outputpath}/{take_id}/{exo_cam}", is_aria=False)
return subsample_idx.tolist()
def decode_mask(width, height, encoded_mask):
try:
decomp_string = LZString.decompressFromEncodedURIComponent(encoded_mask)
except:
return None
decomp_encoded = decomp_string.encode()
rle_obj = {
"size": [height, width],
"counts": decomp_encoded,
}
rle_obj['counts'] = rle_obj['counts'].decode('ascii')
return rle_obj
def processMask(anno, new_anno):
for object_id in anno.keys():
new_anno[object_id] = {}
for cam_id in anno[object_id].keys():
new_anno[object_id][cam_id] = {}
for frame_id in anno[object_id][cam_id]["annotation"].keys():
width = anno[object_id][cam_id]["annotation"][frame_id]["width"]
height = anno[object_id][cam_id]["annotation"][frame_id]["height"]
encoded_mask = anno[object_id][cam_id]["annotation"][frame_id]["encodedMask"]
coco_mask = decode_mask(width, height, encoded_mask)
new_anno[object_id][cam_id][frame_id] = coco_mask
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--takepath",
help="EgoExo take data root",
required=True
)
parser.add_argument(
"--annotationpath",
help="Annotations json file path",
required=True
)
parser.add_argument(
"--split_path",
help="path to split.json",
required=True
)
parser.add_argument(
"--split",
help="train/val/test split to process",
required=True
)
parser.add_argument(
"--outputpath",
help="Output data root",
required=True
)
args = parser.parse_args()
with open(args.split_path, "r") as fp:
data_split = json.load(fp)
# take_list = data_split[args.split]
take_list = ['09417ca4-3572-4ba1-a1db-7eaf3bd0b1c8'] # debug
os.makedirs(args.outputpath, exist_ok=True)
# Read the annotation file
with open(args.annotationpath, "r") as f:
annos = json.load(f)
annos = annos['annotations']
start = time()
for take_id in take_list:
if os.path.exists(f"{args.outputpath}/{take_id}"):
print(f"{take_id} already done!")
continue
# Create the output folder
os.makedirs(f"{args.outputpath}/{take_id}", exist_ok=True)
new_anno = {}
# Get the corresponding take name
anno = annos[take_id]
take_name = anno["take_name"]
valid_cams = set()
for x in anno['object_masks'].keys():
valid_cams.update(set(anno['object_masks'][x].keys()))
ego_cams = []
exo_cams = []
for vc in valid_cams:
if 'aria' in vc:
ego_cams.append(vc)
else:
exo_cams.append(vc)
if len(ego_cams) > 1:
print(take_id, 'HAS MORE THAN ONE EGO')
breakpoint()
print(f"Processing take {take_id} {take_name}")
# Process the masks
print("Start processing masks")
# new_anno["masks"] = {} # debug
# processMask(anno['object_masks'], new_anno["masks"])
# # Process the videos
print("Start processing Videos")
subsample_idx = processVideo(args.takepath, take_name, ego_cam=ego_cams[0], exo_cams=exo_cams, outputpath=args.outputpath, take_id=take_id)
if subsample_idx == -1:
print(f"{args.takepath}/{take_name}/frame_aligned_videos/{ego_cams[0]}.mp4 does not exist")
continue
# new_anno["subsample_idx"] = subsample_idx # debug
# Save the annotation
# with open(f"{args.outputpath}/{take_id}/annotation.json", "w") as f: # debug
# json.dump(new_anno, f)
end = time()
print(f"Total time: {end-start} seconds") |