From 2bf70c58d70233164fd97f76f3f7c1c8e675b8dc Mon Sep 17 00:00:00 2001
From: johnzja <johnzja@qq.com>
Date: Thu, 6 Aug 2020 12:35:32 +0800
Subject: [PATCH] lr0.08_100k

---
 .../fast_scnn_4x8_100k_lr0.08_cityscapes.py   | 61 +++++++++++++++++++
 1 file changed, 61 insertions(+)
 create mode 100644 configs_unify/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py

diff --git a/configs_unify/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py b/configs_unify/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py
new file mode 100644
index 000000000..dac8151f9
--- /dev/null
+++ b/configs_unify/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py
@@ -0,0 +1,61 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 100000
+evaluation = dict(interval=5000, metric='mIoU')
+checkpoint_config = dict(interval=5000)
+