MINIVAL_IDS = [int(line.rstrip('.jpg\n')) for line in f]
with open(EASY_VAL_SMALL_PATH, "r") as f:
EASY_IDS = [int(line.rstrip('.jpg\n')) for line in f]
IMG_NORMALIZE_TRANSFORM = torchvision.transforms.Compose([
# jitter? to gray?
torchvision.transforms.Normalize(mean=IMG_NORM_MEAN,
std=IMG_NORM_STDDEV,
inplace=True)])
AUGMENTATION_TRANSFORM = SeededCompose([
torchvision.transforms.ToPILImage(mode="F"),
torchvision.transforms.RandomHorizontalFlip(p=HORIZONTAL_FLIP_P),
torchvision.transforms.RandomAffine(
degrees=(-ROTATION_MAX_DEGREES, +ROTATION_MAX_DEGREES),
translate=TRANSLATION_MAX_RATIO, scale=SCALE_RANGE),
torchvision.transforms.RandomCrop(size=TRAIN_HW, pad_if_needed=True),
torchvision.transforms.ToTensor()])
minival_dl = torch.utils.data.DataLoader(
CocoDistillationDatasetAugmented2(COCO_DIR, "val2017",
img_transform=IMG_NORMALIZE_TRANSFORM,
remove_images_without_annotations=False,
gt_stddevs_pix=MINIVAL_GT_STDDEVS,
whitelist_ids=MINIVAL_IDS),
batch_size=1,
shuffle=False,
num_workers=0,
pin_memory=True)
MODEL_PATH = "models/pose_higher_hrnet_w48_640.pth.tar"
with open(MINIVAL_FILE, "r") as f:
MINIVAL_IDS = [int(line.rstrip('.jpg\n')) for line in f]
IMG_NORMALIZE_TRANSFORM = torchvision.transforms.Compose([
# jitter? to gray?
torchvision.transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
inplace=True)
])
OVERALL_HHRNET_TRANSFORM = SeededCompose([
torchvision.transforms.ToPILImage(mode="F"),
torchvision.transforms.RandomHorizontalFlip(p=0.5),
torchvision.transforms.RandomAffine(
degrees=(-45, +45), translate=(0.1, 0.1), scale=(0.7, 1.3)),
torchvision.transforms.RandomCrop(size=(480, 480), pad_if_needed=True),
torchvision.transforms.ToTensor()])
# #############################################################################
# # MAIN ROUTINE
# #############################################################################
minival_dataset = CocoDistillationDatasetAugmented(
COCO_DIR, "val2017",
os.path.join(COCO_DIR, "hrnet_predictions", "val2017"),
gt_stddevs_pix=[2.0],
img_transform=IMG_NORMALIZE_TRANSFORM,
whitelist_ids=MINIVAL_IDS)