Merge pull request #1506 from open-mmlab/dev-1.x

Bump Version to 1.0.0rc4

Author: plyfager

.circleci/test.yml

@@ -65,6 +65,7 @@ jobs:
             mim install 'mmdet >= 3.0.0rc2'
             pip install -r requirements/tests.txt
             pip install git+https://github.com/openai/CLIP.git
+            pip install imageio-ffmpeg
       - run:
           name: Build and install
           command: |
@@ -110,6 +111,7 @@ jobs:
             docker exec mmedit mim install 'mmdet >= 3.0.0rc2'
             docker exec mmedit pip install -r requirements/tests.txt
             docker exec mmedit pip install git+https://github.com/openai/CLIP.git
+            docker exec mmedit pip install imageio-ffmpeg
       - run:
           name: Build and install
           command: |

.dev_scripts/update_model_index.py

@@ -16,7 +16,7 @@
 
 import mmengine
 
-MMEditing_ROOT = osp.dirname(osp.dirname(osp.dirname(__file__)))
+MMEditing_ROOT = osp.dirname(osp.dirname(__file__))
 
 all_training_data = [
     'div2k', 'celeba', 'places', 'comp1k', 'vimeo90k', 'reds', 'ffhq', 'cufed',
@@ -156,6 +156,8 @@ def parse_md(md_file):
         collection['Name'] = name
         collection_name = name
         is_liif = collection_name.upper() == 'LIIF'
+        task_line = lines[4]
+        task = task_line.strip().split(':')[-1].strip()
         while i < len(lines):
             # parse reference
             if lines[i].startswith('> ['):
@@ -202,7 +204,6 @@ def parse_md(md_file):
 
                 j = i + 2
                 while j < len(lines) and lines[j][0] == '|':
-                    task = get_task_name(md_file)
                     line = lines[j].split('|')[1:-1]
 
                     if line[config_idx].find('](') >= 0:

.github/workflows/merge_stage_test.yml

@@ -50,6 +50,7 @@ jobs:
         run: |
           pip install -r requirements/tests.txt
           pip install git+https://github.com/openai/CLIP.git
+          pip install imageio-ffmpeg
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Run unittests and generate coverage report
@@ -100,6 +101,8 @@ jobs:
         run: |
           pip install -r requirements/tests.txt
           pip install git+https://github.com/openai/CLIP.git
+          pip install imageio-ffmpeg
+
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Run unittests and generate coverage report
@@ -154,6 +157,7 @@ jobs:
           pip install -U openmim
           mim install 'mmcv >= 2.0.0rc1'
           pip install -r requirements/tests.txt
+          pip install imageio-ffmpeg
       - name: Build and install
         run: |
           python setup.py check -m -s
@@ -186,6 +190,7 @@ jobs:
           mim install 'mmdet >= 3.0.0rc2'
           python -m pip install -r requirements/tests.txt
           python -m pip install git+https://github.com/openai/CLIP.git
+          python -m pip install imageio-ffmpeg
       - name: Build and install
         run: |
           python -m pip install -e .

.github/workflows/pr_stage_test.yml

@@ -44,6 +44,7 @@ jobs:
         run: |
           pip install -r requirements/tests.txt
           pip install git+https://github.com/openai/CLIP.git
+          pip install imageio-ffmpeg
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Run unittests and generate coverage report
@@ -100,6 +101,7 @@ jobs:
           mim install 'mmdet >= 3.0.0rc2'
           pip install -r requirements/tests.txt
           pip install git+https://github.com/openai/CLIP.git
+          pip install imageio-ffmpeg
       - name: Build and install
         run: |
           python setup.py check -m -s
@@ -135,6 +137,7 @@ jobs:
           mim install 'mmdet >= 3.0.0rc2'
           python -m pip install -r requirements/tests.txt
           pip install git+https://github.com/openai/CLIP.git
+          python -m pip install imageio-ffmpeg
       - name: Build and install
         run: |
           python -m pip install -e .

.readthedocs.yml

@@ -7,3 +7,4 @@ python:
     install:
       - requirements: requirements/docs.txt
       - requirements: requirements/readthedocs.txt
+      - requirements: requirements/runtime.txt

README.md

@@ -106,13 +106,14 @@ hope MMEditing could provide better experience.
 
 ### 🌟 Preview of 1.x version
 
-A brand new version of [**MMEditing v1.0.0rc3**](https://github.com/open-mmlab/mmediting/releases/tag/v1.0.0rc3) was released in 09/11/2022:
+A brand new version of [**MMEditing v1.0.0rc4**](https://github.com/open-mmlab/mmediting/releases/tag/v1.0.0rc4) was released in 05/12/2022:
 
-- Support all the tasks, models, metrics, and losses in [MMGeneration](https://github.com/open-mmlab/mmgeneration) 😍。
+- Support Text2Image Task! [Disco-Diffusion](configs/disco_diffusion/README.md)
+- Support 3D-aware Generation Task! [EG3D](configs/eg3d/README.md)
+- Support all the tasks, models, metrics, and losses in [MMGeneration](https://github.com/open-mmlab/mmgeneration) 😍.
 - Unifies interfaces of all components based on [MMEngine](https://github.com/open-mmlab/mmengine).
 - Support patch-based and slider-based image and video comparison viewer.
 - Support image colorization.
-- Convert `mmdet` and `clip` to optional requirements.
 
 Find more new features in [1.x branch](https://github.com/open-mmlab/mmediting/tree/1.x). Issues and PRs are welcome!
 
@@ -266,6 +267,21 @@ Supported algorithms:
 
 </details>
 
+<details open>
+<summary>Text2Image</summary>
+
+- ✅ [Disco-Diffusion](configs/disco_diffusion/README.md)
+
+</details>
+
+<details open>
+
+<summary>3D-aware Generation</summary>
+
+- ✅ [EG3D](configs/eg3d/README.md)
+
+</details>
+
 Please refer to [model_zoo](https://mmediting.readthedocs.io/en/1.x/3_model_zoo.html) for more details.
 
 ## Contributing

README_zh-CN.md

@@ -105,13 +105,14 @@ MMEditing 缜密地设计新的框架并将其精心实现，希望能够为您
 
 ### 🌟 1.x 预览版本
 
-全新的 [**MMEditing v1.0.0rc3**](https://github.com/open-mmlab/mmediting/releases/tag/v1.0.0rc3) 已经在 09/11/2022 发布:
+全新的 [**MMEditing v1.0.0rc4**](https://github.com/open-mmlab/mmediting/releases/tag/v1.0.0rc4) 已经在 05/12/2022 发布:
 
+- 支持了图文生成任务! [Disco-Diffusion](configs/disco_diffusion/README.md)
+- 支持了3D级图像生成任务! [EG3D](configs/eg3d/README.md)
 - 支持[MMGeneration](https://github.com/open-mmlab/mmgeneration)中的全量任务、模型、优化函数和评价指标 😍。
 - 基于[MMEngine](https://github.com/open-mmlab/mmengine)统一了各组件接口。
 - 支持基于图像子块以及滑动条的图像和视频比较可视化工具。
 - 支持图像上色任务。
-- 将 `mmdet` 与 `clip` 切换为可选依赖
 
 在[1.x 分支](https://github.com/open-mmlab/mmediting/tree/1.x)中发现更多特性！欢迎提 Issues 和 PRs！
 
@@ -264,6 +265,21 @@ pip3 install -e .
 
 </details>
 
+<details open>
+<summary>Text2Image</summary>
+
+- ✅ [Disco-Diffusion](configs/disco_diffusion/README.md)
+
+</details>
+
+<details open>
+
+<summary>3D-aware Generation</summary>
+
+- ✅ [EG3D](configs/eg3d/README.md)
+
+</details>
+
 请参考[模型库](https://mmediting.readthedocs.io/zh_CN/1.x/3_model_zoo.html)了解详情。
 
 ## 参与贡献
@@ -316,10 +332,10 @@ MMEditing 是一款由不同学校和公司共同贡献的开源项目。我们
 
 ## 欢迎加入 OpenMMLab 社区
 
-扫描下方的二维码可关注 OpenMMLab 团队的 [知乎官方账号](https://www.zhihu.com/people/openmmlab)，加入 OpenMMLab 团队的 [官方交流 QQ 群](https://jq.qq.com/?_wv=1027&k=GJP18SjI)，或通过群主小喵加入微信官方交流群。
+扫描下方的二维码可关注 OpenMMLab 团队的 [知乎官方账号](https://www.zhihu.com/people/openmmlab)，加入 OpenMMLab 团队的 [官方交流 QQ 群](https://jq.qq.com/?_wv=1027&k=K0QI8ByU)，或通过群主小喵加入微信官方交流群。
 
 <div align="center">
-<img src="docs/zh_cn/_static/image/zhihu_qrcode.jpg" height="500" />  <img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/qq_group_qrcode.jpg" height="500" /> <img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/wechat_qrcode.jpg" height="500" />
+<img src="docs/zh_cn/_static/image/zhihu_qrcode.jpg" height="500" />  <img src="https://user-images.githubusercontent.com/25839884/203927852-e15def4d-a0eb-4dfc-9bfb-7cf09ea945d0.png" height="500" /> <img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/wechat_qrcode.jpg" height="500" />
 </div>
 
 我们会在 OpenMMLab 社区为大家

configs/_base_/datasets/grow_scale_imgs_ffhq_styleganv1.py

@@ -36,7 +36,7 @@
     num_workers=4,
     batch_size=64,
     dataset=dict(
-        type='UnconditionalImageDataset',
+        type='BasicImageDataset',
         pipeline=pipeline,
         data_root='./data/ffhq/images'),
     sampler=dict(type='DefaultSampler', shuffle=False))

configs/_base_/datasets/imagenet_512.py

@@ -0,0 +1,45 @@
+# dataset settings
+dataset_type = 'ImageNet'
+
+# different from mmcls, we adopt the setting used in BigGAN.
+# We use `RandomCropLongEdge` in training and `CenterCropLongEdge` in testing.
+train_pipeline = [
+    dict(type='LoadImageFromFile', key='img'),
+    dict(type='RandomCropLongEdge', keys=['img']),
+    dict(type='Resize', scale=(512, 512), keys=['img'], backend='pillow'),
+    dict(type='Flip', flip_ratio=0.5, direction='horizontal'),
+    dict(type='PackEditInputs')
+]
+
+test_pipeline = [
+    dict(type='LoadImageFromFile', key='img'),
+    dict(type='CenterCropLongEdge', keys=['img']),
+    dict(type='Resize', scale=(512, 512), backend='pillow'),
+    dict(type='PackEditInputs')
+]
+
+train_dataloader = dict(
+    batch_size=None,
+    num_workers=5,
+    dataset=dict(
+        type=dataset_type,
+        data_root='./data/imagenet/',
+        ann_file='meta/train.txt',
+        data_prefix='train',
+        pipeline=train_pipeline),
+    sampler=dict(type='DefaultSampler', shuffle=True),
+    persistent_workers=True)
+
+val_dataloader = dict(
+    batch_size=None,
+    num_workers=5,
+    dataset=dict(
+        type=dataset_type,
+        data_root='./data/imagenet/',
+        ann_file='meta/train.txt',
+        data_prefix='train',
+        pipeline=test_pipeline),
+    sampler=dict(type='DefaultSampler', shuffle=False),
+    persistent_workers=True)
+
+test_dataloader = val_dataloader

configs/_base_/datasets/imagenet_64.py

@@ -0,0 +1,45 @@
+# dataset settings
+dataset_type = 'ImageNet'
+
+# different from mmcls, we adopt the setting used in BigGAN.
+# We use `RandomCropLongEdge` in training and `CenterCropLongEdge` in testing.
+train_pipeline = [
+    dict(type='LoadImageFromFile', key='img'),
+    dict(type='RandomCropLongEdge', keys=['img']),
+    dict(type='Resize', scale=(64, 64), keys=['img'], backend='pillow'),
+    dict(type='Flip', flip_ratio=0.5, direction='horizontal'),
+    dict(type='PackEditInputs')
+]
+
+test_pipeline = [
+    dict(type='LoadImageFromFile', key='img'),
+    dict(type='CenterCropLongEdge', keys=['img']),
+    dict(type='Resize', scale=(64, 64), backend='pillow'),
+    dict(type='PackEditInputs')
+]
+
+train_dataloader = dict(
+    batch_size=None,
+    num_workers=5,
+    dataset=dict(
+        type=dataset_type,
+        data_root='./data/imagenet/',
+        ann_file='meta/train.txt',
+        data_prefix='train',
+        pipeline=train_pipeline),
+    sampler=dict(type='DefaultSampler', shuffle=True),
+    persistent_workers=True)
+
+val_dataloader = dict(
+    batch_size=64,
+    num_workers=5,
+    dataset=dict(
+        type=dataset_type,
+        data_root='./data/imagenet/',
+        ann_file='meta/train.txt',
+        data_prefix='train',
+        pipeline=test_pipeline),
+    sampler=dict(type='DefaultSampler', shuffle=False),
+    persistent_workers=True)
+
+test_dataloader = val_dataloader