From 107b54da6af83ace73d1ce6d8f46909876076bde Mon Sep 17 00:00:00 2001
From: "Wu, Jiantao (PG/R - Comp Sci & Elec Eng)" <jiantao.wu@surrey.ac.uk>
Date: Wed, 28 Feb 2024 13:57:53 +0000
Subject: [PATCH] change dres
---
vitookit/datasets/dres.py | 70 +++++++++++++++++++++++++
vitookit/datasets/ffcv_transform.py | 78 ----------------------------
vitookit/datasets/sa.py | 6 +--
vitookit/datasets/transform.py | 5 +-
vitookit/evaluation/eval_cls_ffcv.py | 8 +--
5 files changed, 78 insertions(+), 89 deletions(-)
create mode 100644 vitookit/datasets/dres.py
diff --git a/vitookit/datasets/dres.py b/vitookit/datasets/dres.py
new file mode 100644
index 0000000..9d6d149
--- /dev/null
+++ b/vitookit/datasets/dres.py
@@ -0,0 +1,70 @@
+
+from ffcv import Loader
+import gin
+from .ffcv_transform import ThreeAugmentPipeline
+
+@gin.configurable
+class DynamicResolution:
+ def __init__(self, start_ramp=gin.REQUIRED, end_ramp=gin.REQUIRED,
+ scheme=1):
+ schemes ={
+ 1: [
+ dict(res=160,lower_scale=0.08, upper_scale=1,color_jitter=False),
+ dict(res=192,lower_scale=0.08, upper_scale=1,color_jitter=False),
+ dict(res=224,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ ],
+ 2:[
+ dict(res=160,lower_scale=0.96, upper_scale=1,color_jitter=False),
+ dict(res=192,lower_scale=0.38, upper_scale=1,color_jitter=False),
+ dict(res=224,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ ],
+ 3:[
+ dict(res=160,lower_scale=0.08, upper_scale=0.4624,color_jitter=False),
+ dict(res=192,lower_scale=0.08, upper_scale=0.7056,color_jitter=False),
+ dict(res=224,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ ],
+ 4:[
+ dict(res=160,lower_scale=0.20, upper_scale=0.634,color_jitter=False),
+ dict(res=192,lower_scale=0.137, upper_scale=0.81,color_jitter=False),
+ dict(res=224,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ ],
+ 5: [
+ dict(res=160,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ dict(res=192,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ dict(res=224,lower_scale=0.08, upper_scale=1,color_jitter=True),
+ ],
+
+ }
+ self.scheme = schemes[scheme]
+ self.start_ramp = start_ramp
+ self.end_ramp = end_ramp
+
+
+ def get_config(self, epoch):
+ if epoch <= self.start_ramp:
+ return self.scheme[0]
+ elif epoch>=self.end_ramp:
+ return self.scheme[-1]
+ else:
+ i = (epoch-self.start_ramp) * (len(self.scheme)-1) // (self.end_ramp-self.start_ramp)
+ return self.scheme[i]
+
+ def __call__(self, loader: Loader, epoch,is_ffcv=False):
+ config = self.get_config(epoch)
+ print(", ".join([f"{k}={v}" for k,v in config.items()]))
+
+ img_size = config['res']
+ lower_scale = config['lower_scale']
+ upper_scale = config['upper_scale']
+ color_jitter = config['color_jitter']
+
+ if is_ffcv:
+ pipelines = ThreeAugmentPipeline(img_size,scale=(lower_scale,upper_scale),color_jitter=color_jitter)
+ loader.compile_pipeline(pipelines)
+ else:
+ # todo: change dres
+ pipelines = loader.dataset.transforms
+
+ decoder = loader.dataset.transforms.transform.transforms[0]
+ decoder.size=(img_size,img_size)
+ decoder.scale = (lower_scale,upper_scale)
diff --git a/vitookit/datasets/ffcv_transform.py b/vitookit/datasets/ffcv_transform.py
index ae25390..db86abc 100644
--- a/vitookit/datasets/ffcv_transform.py
+++ b/vitookit/datasets/ffcv_transform.py
@@ -36,84 +36,6 @@ IMAGENET_MEAN = np.array([0.485, 0.456, 0.406]) * 255
IMAGENET_STD = np.array([0.229, 0.224, 0.225]) * 255
-@gin.configurable
-class DynamicResolution:
- def __init__(self, start_ramp=gin.REQUIRED, end_ramp=gin.REQUIRED,
- scheme=1):
- schemes ={
- 1: [
- dict(res=160,lower_scale=0.08, upper_scale=1),
- dict(res=192,lower_scale=0.08, upper_scale=1),
- dict(res=224,lower_scale=0.08, upper_scale=1),
- ],
- 2:[
- dict(res=160,lower_scale=0.96, upper_scale=1),
- dict(res=192,lower_scale=0.38, upper_scale=1),
- dict(res=224,lower_scale=0.08, upper_scale=1),
- ],
- 3:[
- dict(res=160,lower_scale=0.08, upper_scale=0.4624),
- dict(res=192,lower_scale=0.08, upper_scale=0.7056),
- dict(res=224,lower_scale=0.08, upper_scale=1),
- ],
- 4:[
- dict(res=160,lower_scale=0.20, upper_scale=0.634),
- dict(res=192,lower_scale=0.137, upper_scale=0.81),
- dict(res=224,lower_scale=0.08, upper_scale=1),
- ],
- 5: [
- dict(res=160,lower_scale=0.20, upper_scale=1),
- dict(res=192,lower_scale=0.137, upper_scale=1),
- dict(res=224,lower_scale=0.08, upper_scale=1),
- ],
-
- }
- self.scheme = schemes[scheme]
- self.start_ramp = start_ramp
- self.end_ramp = end_ramp
-
-
- def get_resolution(self, epoch):
- if epoch<=(self.start_ramp+self.end_ramp)/2:
- return self.scheme[0]['res']
- elif epoch<=self.end_ramp:
- return self.scheme[1]['res']
- else:
- return self.scheme[2]['res']
-
- def get_lower_scale(self, epoch):
- if epoch<=(self.start_ramp+self.end_ramp)/2:
- return self.scheme[0]['lower_scale']
- elif epoch<=self.end_ramp:
- return self.scheme[1]['lower_scale']
- else:
- return self.scheme[2]['lower_scale']
-
- def get_upper_scale(self, epoch):
- if epoch<=(self.start_ramp+self.end_ramp)/2:
- return self.scheme[0]['upper_scale']
- elif epoch<=self.end_ramp:
- return self.scheme[1]['upper_scale']
- else:
- return self.scheme[2]['upper_scale']
-
- def __call__(self, loader, epoch,is_ffcv=False):
- img_size = self.get_resolution(epoch)
- lower_scale = self.get_lower_scale(epoch)
- upper_scale = self.get_upper_scale(epoch)
- print(f"resolution = {img_size}, scale = ({lower_scale:.2f},{upper_scale:.2f}) ")
-
- if is_ffcv:
- pipeline=loader.pipeline_specs['image']
- if pipeline.decoder.output_size[0] != img_size:
- pipeline.decoder.scale = (lower_scale,upper_scale)
- pipeline.decoder.output_size = (img_size,img_size)
- loader.generate_code()
- else:
- decoder = loader.dataset.transforms.transform.transforms[0]
- decoder.size=(img_size,img_size)
- decoder.scale = (lower_scale,upper_scale)
-
@gin.configurable
def SimplePipeline(img_size=224,scale=(0.2,1), ratio=(3.0/4.0, 4.0/3.0)):
image_pipeline = [
diff --git a/vitookit/datasets/sa.py b/vitookit/datasets/sa.py
index 38e7aed..a5e5ff7 100644
--- a/vitookit/datasets/sa.py
+++ b/vitookit/datasets/sa.py
@@ -117,6 +117,6 @@ class SA1BDataset:
m = maskUtils.decode(rle)
return m
-
-data=SA1BDataset('/vol/research/datasets/still/SA-1B',['sa_258805','sa_2601447','sa_6313499','sa_2592075','sa_258406','sa_2601844','sa_6353015','sa_10958302','sa_6344773']) # if you want a subset of the dataset
-img, mask, class_ids = data[0]
\ No newline at end of file
+if __name__ == '__main__':
+ data=SA1BDataset('/vol/research/datasets/still/SA-1B',['sa_258805','sa_2601447','sa_6313499','sa_2592075','sa_258406','sa_2601844','sa_6353015','sa_10958302','sa_6344773']) # if you want a subset of the dataset
+ img, mask, class_ids = data[0]
\ No newline at end of file
diff --git a/vitookit/datasets/transform.py b/vitookit/datasets/transform.py
index 5d017f7..a628005 100644
--- a/vitookit/datasets/transform.py
+++ b/vitookit/datasets/transform.py
@@ -5,7 +5,7 @@ import numpy as np
from torchvision import transforms
import torch
import gin
-
+from torch import nn
class PermutePatch(object):
"""
@@ -103,6 +103,9 @@ class GrayScale(object):
else:
return img
+class ThreeAugmentation(nn.Module):
+ def __init__(self,):
+ super().__init__()
def three_augmentation(args = None):
img_size = args.input_size
diff --git a/vitookit/evaluation/eval_cls_ffcv.py b/vitookit/evaluation/eval_cls_ffcv.py
index fa9e32a..2450174 100644
--- a/vitookit/evaluation/eval_cls_ffcv.py
+++ b/vitookit/evaluation/eval_cls_ffcv.py
@@ -43,7 +43,7 @@ from timm.layers import trunc_normal_
from ffcv import Loader
from ffcv.loader import OrderOption
-
+from datasets.dres import DynamicResolution
def get_args_parser():
parser = argparse.ArgumentParser('DeiT training and evaluation script', add_help=False)
@@ -342,12 +342,6 @@ def main(args):
for epoch in range(args.start_epoch, args.epochs):
if dres:
- if epoch == dres.end_ramp:
- print("enhance augmentation!", epoch, dres.end_ramp)
- ## enhance augmentation, see efficientnetv2
- data_loader_train = Loader(args.train_path, pipelines=ThreeAugmentPipeline(color_jitter=0.3),
- batch_size=args.batch_size, num_workers=args.num_workers,
- order=order, distributed=args.distributed,seed=args.seed)
dres(data_loader_train,epoch,True)
train_stats = train_one_epoch(
--
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