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TRAIN, VALIDATION, SCHEDULER, REDUCELRONPLATEAU,
MODEL, ARCHITECTURE, ID, NAME, SCHEDULER_CONFIGURATION, OPTIMIZER, PARAMS, LR,
LOSS, LOSS_MSE, CONFIG_DEAD_LEAVES,
SELECTED_METRICS, METRIC_PSNR, METRIC_SSIM, METRIC_LPIPS,
DATASET_DL_DIV2K_512, DATASET_DIV2K,
CONFIG_DEGRADATION,
PRETTY_NAME,
DEGRADATION_BLUR_NONE, DEGRADATION_BLUR_MAT, DEGRADATION_BLUR_GAUSS,
AUGMENTATION_FLIP, AUGMENTATION_ROTATE,
DATASET_DL_EXTRAPRIMITIVES_DIV2K_512)
from typing import Tuple
def model_configurations(config, model_preset="StackedConvolutions", bias: bool = True) -> dict:
if model_preset == "StackedConvolutions":
config[MODEL] = {
ARCHITECTURE: dict(
num_layers=8,
k_size=3,
h_dim=16,
bias=bias
),
NAME: "StackedConvolutions"
}
elif model_preset == "NAFNet" or model_preset == "UNet":
# https://github.com/megvii-research/NAFNet/blob/main/options/test/GoPro/NAFNet-width64.yml
config[MODEL] = {
ARCHITECTURE: dict(
width=64,
enc_blk_nums=[1, 1, 1, 28],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1, 1],
),
NAME: model_preset
}
else:
raise ValueError(f"Unknown model preset {model_preset}")
def presets_experiments(
exp: int,
b: int = 32,
n: int = 50,
bias: bool = True,
length: int = 5000,
data_size: Tuple[int, int] = (128, 128),
model_preset: str = "StackedConvolutions",
lpips: bool = False
) -> dict:
config = {
ID: exp,
NAME: f"{exp:04d}",
NB_EPOCHS: n
}
config[DATALOADER] = {
BATCH_SIZE: {
TRAIN: b,
VALIDATION: b
},
SIZE: data_size, # (width, height)
LENGTH: {
TRAIN: length,
VALIDATION: 800
}
}
config[OPTIMIZER] = {
NAME: "Adam",
PARAMS: {
LR: 1e-3
}
}
model_configurations(config, model_preset=model_preset, bias=bias)
config[SCHEDULER] = REDUCELRONPLATEAU
config[SCHEDULER_CONFIGURATION] = {
"factor": 0.8,
"patience": 5
}
config[LOSS] = LOSS_MSE
config[SELECTED_METRICS] = [METRIC_PSNR, METRIC_SSIM]
if lpips:
config[SELECTED_METRICS].append(METRIC_LPIPS)
return config
def get_experiment_config(exp: int) -> dict:
if exp == -1:
config = presets_experiments(exp, length=10, n=2)
elif exp == -2:
config = presets_experiments(exp, length=10, n=2, lpips=True)
elif exp == -3:
config = presets_experiments(exp, n=20)
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla denoise only - ds=1 - noisy 0-50"
elif exp == -4:
config = presets_experiments(exp, b=4, n=20)
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla exp from disk - noisy 0-50"
elif exp == 1000:
config = presets_experiments(exp, n=60)
config[PRETTY_NAME] = "Vanilla small blur"
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 2], ds_factor=1, noise_stddev=[0., 0.])
elif exp == 1001:
config = presets_experiments(exp, n=60)
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 6], ds_factor=1, noise_stddev=[0., 0.])
config[PRETTY_NAME] = "Vanilla large blur 0 - 6"
elif exp == 1002:
config = presets_experiments(exp, n=6) # Less epochs because of the large downsample factor
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 2], ds_factor=5, noise_stddev=[0., 0.])
config[PRETTY_NAME] = "Vanilla small blur - ds=5"
elif exp == 1003:
config = presets_experiments(exp, n=6) # Less epochs because of the large downsample factor
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 2], ds_factor=5, noise_stddev=[0., 50.])
config[PRETTY_NAME] = "Vanilla small blur - ds=5 - noisy 0-50"
elif exp == 1004:
config = presets_experiments(exp, n=60)
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 0], ds_factor=1, noise_stddev=[0., 50.])
config[PRETTY_NAME] = "Vanilla denoise only - ds=1 - noisy 0-50"
elif exp == 1005:
config = presets_experiments(exp, bias=False, n=60)
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 0], ds_factor=1, noise_stddev=[0., 50.])
config[PRETTY_NAME] = "Vanilla denoise only - ds=1 - noisy 0-50 - bias free"
elif exp == 1006:
config = presets_experiments(exp, n=60)
config[PRETTY_NAME] = "Vanilla small blur - noisy 0-50"
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 2], ds_factor=1, noise_stddev=[0., 50.])
elif exp == 1007:
config = presets_experiments(exp, n=60)
config[PRETTY_NAME] = "Vanilla large blur 0 - 6 - noisy 0-50"
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(blur_kernel_half_size=[0, 6], ds_factor=1, noise_stddev=[0., 50.])
elif exp == 2000:
config = presets_experiments(exp, n=60, b=16, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet denoise 0-50"
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
elif exp == 2001:
config = presets_experiments(exp, n=60, b=16, model_preset="UNet")
config[PRETTY_NAME] = "UNEt denoise 0-50"
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
elif exp == 2002:
config = presets_experiments(exp, n=20, b=8, data_size=(256, 256), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet denoise 0-50 gpu dl 256x256"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
elif exp == 2003:
config = presets_experiments(exp, n=20, b=8, data_size=(128, 128), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet denoise 0-50 gpu dl - 128x128"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
elif exp == 2004:
config = presets_experiments(exp, n=20, b=16, data_size=(128, 128), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet Light denoise 0-50 gpu dl - 128x128"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1, 1],
)
elif exp == 2005:
config = presets_experiments(exp, n=20, b=16, data_size=(128, 128), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet TresLight denoise 0-50 gpu dl - 128x128"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=1,
noise_stddev=[0., 50.]
)
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
elif exp == 2006:
config = presets_experiments(exp, n=20, b=16, data_size=(128, 128), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet TresLight denoise 0-50 ds=5 gpu dl - 128x128"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=5,
noise_stddev=[0., 50.]
)
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
elif exp == 2007:
config = presets_experiments(exp, n=20, b=16, data_size=(128, 128), model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet denoise 0-50 gpu dl -ds=5 128x128"
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=5,
noise_stddev=[0., 50.]
)
elif exp == 1008:
config = presets_experiments(exp, n=20)
config[DATALOADER]["gpu_gen"] = True
config[DATALOADER][CONFIG_DEAD_LEAVES] = dict(
blur_kernel_half_size=[0, 0],
ds_factor=5,
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla denoise only - ds=5 - noisy 0-50"
# ---------------------------------
# Pure DL DENOISING trainings!
# ---------------------------------
elif exp == 3000:
config = presets_experiments(exp, n=30, b=4, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet denoise - DL_DIV2K_512 0-50"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 3001: # ENABLE GRADIENT CLIPPING
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet41.4M denoise - DL_DIV2K_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 3002: # ENABLE GRADIENT CLIPPING
config = presets_experiments(exp, n=30, b=16, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet41.4M denoise - DL_DIV2K_512 0-50 128x128"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[DATALOADER][SIZE] = (128, 128)
elif exp == 3010 or exp == 3011: # exp 3011 = REDO with Gradient clipping
config = presets_experiments(exp, n=50, b=4, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet3.4M Light denoise - DL_DIV2K_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 3020:
config = presets_experiments(exp, b=32, n=50)
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla denoise DL 0-50 - noisy 0-50"
# ---------------------------------
# Pure DIV2K DENOISING trainings!
# ---------------------------------
elif exp == 3120:
config = presets_experiments(exp, b=32, n=50)
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla DIV2K_512 0-50 - noisy 0-50"
elif exp == 3111:
config = presets_experiments(exp, n=50, b=4, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet3.4M Light denoise - DIV2K_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(noise_stddev=[0., 50.])
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 3101:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet41.4M denoise - DIV2K_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[DATALOADER][SIZE] = (256, 256)
# ---------------------------------
# Pure EXTRA PRIMITIVES
# ---------------------------------
elif exp == 3030:
config = presets_experiments(exp, b=128, n=50)
config[DATALOADER][NAME] = DATASET_DL_EXTRAPRIMITIVES_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.]
)
config[PRETTY_NAME] = "Vanilla DL_PRIMITIVES_512 0-50 - noisy 0-50"
# config[DATALOADER][SIZE] = (256, 256)
elif exp == 3040:
config = presets_experiments(exp, n=50, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet3.4M Light denoise - DL_PRIMITIVES_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DL_EXTRAPRIMITIVES_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(noise_stddev=[0., 50.])
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 3050:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet41.4M denoise - DL_PRIMITIVES_512 0-50 256x256"
config[DATALOADER][NAME] = DATASET_DL_EXTRAPRIMITIVES_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(noise_stddev=[0., 50.])
config[DATALOADER][SIZE] = (256, 256)
# ---------------------------------
# DEBLURRING
# ---------------------------------
elif exp == 5000:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet deblur - DL_DIV2K_512 256x256"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 5001:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet deblur - DIV2K_512 256x256"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 5002:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet deblur - DL_DIV2K_512 256x256"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 5003:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet deblur - DIV2K_512 256x256"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 5004:
config = presets_experiments(exp, n=30, b=8, model_preset="NAFNet")
config[PRETTY_NAME] = "NAFNet deblur - DIV2K_512 256x256"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
elif exp == 5005:
config = presets_experiments(exp, n=30, b=8, model_preset="UNet")
config[PRETTY_NAME] = "UNet deblur - DL_512 256x256"
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
# elif exp == 6000: # -> FAILED, no kernels normalization!
# config = presets_experiments(exp, b=32, n=50)
# config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
# config[DATALOADER][CONFIG_DEGRADATION] = dict(
# noise_stddev=[0., 50.],
# degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
# augmentation_list=[AUGMENTATION_FLIP]
# )
# config[PRETTY_NAME] = "Vanilla deblur DL_DIV2K_512"
elif exp == 6002:
config = presets_experiments(exp, b=128, n=50)
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.],
degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[PRETTY_NAME] = "Vanilla deblur DL_DIV2K_512"
# elif exp == 6001: # -> FAILED, no kernels normalization!
# config = presets_experiments(exp, b=32, n=50)
# config[DATALOADER][NAME] = DATASET_DIV2K
# config[DATALOADER][CONFIG_DEGRADATION] = dict(
# noise_stddev=[0., 50.],
# degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
# augmentation_list=[AUGMENTATION_FLIP]
# )
# config[PRETTY_NAME] = "Vanilla delbur DIV2K_512"
elif exp == 6003:
config = presets_experiments(exp, b=128, n=50)
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.],
degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[PRETTY_NAME] = "Vanilla delbur DIV2K_512"
elif exp == 7000:
config = presets_experiments(exp, b=16, n=30, model_preset="NAFNet")
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
config[DATALOADER][NAME] = DATASET_DL_DIV2K_512
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.],
degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[PRETTY_NAME] = "NafNet Light deblur DL"
config[DATALOADER][SIZE] = (256, 256)
elif exp == 7001:
config = presets_experiments(exp, b=16, n=50, model_preset="NAFNet")
config[DATALOADER][NAME] = DATASET_DIV2K
config[MODEL][ARCHITECTURE] = dict(
width=64,
enc_blk_nums=[1, 1, 2],
middle_blk_num=1,
dec_blk_nums=[1, 1, 1],
)
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 50.],
degradation_blur=DEGRADATION_BLUR_MAT, # Deblur = Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[PRETTY_NAME] = "NafNet Light deblur DIV2K"
config[DATALOADER][SIZE] = (256, 256)
elif exp == 7002:
config = presets_experiments(exp, n=20, b=8, model_preset="UNet")
config[PRETTY_NAME] = "UNET deblur - DIV2K"
config[DATALOADER][NAME] = DATASET_DIV2K
config[DATALOADER][CONFIG_DEGRADATION] = dict(
noise_stddev=[0., 0.],
degradation_blur=DEGRADATION_BLUR_MAT, # Using .mat kernels
augmentation_list=[AUGMENTATION_FLIP]
)
config[DATALOADER][SIZE] = (256, 256)
else:
raise ValueError(f"Experiment {exp} not found")
return config
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