Merge pull request RangiLyu#289 from RangiLyu/refactor/code_quality

[Refactor] code quality
AlongRide · Jul 18, 2021 · 480ee5a · 480ee5a
2 parents be08279 + 46a4962
commit 480ee5a
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diff --git a/.flake8 b/.flake8
@@ -0,0 +1,11 @@
+# This is an example .flake8 config, used when developing *Black* itself.
+# Keep in sync with setup.cfg which is used for source packages.
+
+[flake8]
+ignore = W503, E203, E221, C901, C408, E741, C407, E741, B006, B007, B017, B950, C416
+max-line-length = 88
+max-complexity = 18
+select = B,C,E,F,W,T4,B9
+exclude = build
+per-file-ignores =
+  **/__init__.py:F401,F403,E402
diff --git a/.github/workflows/workflow.yml b/.github/workflows/workflow.yml
@@ -0,0 +1,121 @@
+name: CI
+on: [push, pull_request]
+
+jobs:
+  linter:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.6
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.6
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install flake8==3.9.2 flake8-bugbear flake8-comprehensions isort==5.8.0
+          python -m pip install black==21.6b0
+          flake8 --version
+      - name: Lint
+        run: |
+          echo "Running isort"
+          isort --profile black .
+          echo "Running black"
+          black --check .
+          echo "Running flake8"
+          flake8 .
+
+  test_cpu:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        torch: [1.6.0, 1.7.0, 1.8.0]
+        include:
+          - torch: 1.6.0
+            torchvision: 0.7.0
+          - torch: 1.7.0
+            torchvision: 0.8.1
+          - torch: 1.8.0
+            torchvision: 0.9.0
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Set up Python 3.6
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.6
+      - name: Install dependencies
+        run: |
+          python -m pip install -U pip
+          python -m pip install ninja opencv-python-headless onnx pytest-xdist codecov
+          python -m pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+          python -m pip install Cython termcolor numpy tensorboard pycocotools matplotlib pyaml opencv-python tqdm pytorch-lightning torchmetrics codecov flake8 pytest
+      - name: Setup
+        run: rm -rf .eggs && python setup.py develop
+      - name: Run unittests and generate coverage report
+        run: |
+          coverage run --branch --source nanodet -m pytest tests/
+          coverage xml
+          coverage report -m
+
+  test_cuda:
+    runs-on: ubuntu-latest
+    env:
+      CUDA: 10.1.105-1
+      CUDA_SHORT: 10.1
+      UBUNTU_VERSION: ubuntu1804
+    strategy:
+      matrix:
+        torch: [1.6.0+cu101, 1.7.0+cu101, 1.8.0+cu101]
+        include:
+          - torch: 1.6.0+cu101
+            torchvision: 0.7.0+cu101
+          - torch: 1.7.0+cu101
+            torchvision: 0.8.1+cu101
+          - torch: 1.8.0+cu101
+            torchvision: 0.9.0+cu101
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Set up Python 3.6
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.6
+      - name: Install CUDA
+        run: |
+          export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
+          wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
+          sudo dpkg -i ${INSTALLER}
+          wget https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
+          sudo apt-key add 7fa2af80.pub
+          sudo apt update -qq
+          sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-}
+          sudo apt clean
+          export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
+          export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH}
+          export PATH=${CUDA_HOME}/bin:${PATH}
+      - name: Install dependencies
+        run: |
+          python -m pip install -U pip
+          python -m pip install ninja opencv-python-headless onnx pytest-xdist codecov
+          python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+          python -m pip install Cython termcolor numpy tensorboard pycocotools matplotlib pyaml opencv-python tqdm pytorch-lightning torchmetrics codecov flake8 pytest
+      - name: Setup
+        run: |
+          rm -rf .eggs
+          python setup.py check -m -s
+          TORCH_CUDA_ARCH_LIST=7.0 pip install .
+      - name: Run unittests and generate coverage report
+        run: |
+          coverage run --branch --source nanodet -m pytest tests/
+          coverage xml
+          coverage report -m
+      - name: Upload coverage to Codecov
+        uses: codecov/[email protected]
+        if: matrix.torch == '1.8.0+cu101'
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false
diff --git a/.isort.cfg b/.isort.cfg
@@ -0,0 +1,2 @@
+[tool.isort]
+profile = "black"
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -0,0 +1,26 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v2.5.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-docstring-first
+      - id: check-yaml
+      - id: debug-statements
+      - id: requirements-txt-fixer
+
+  - repo: https://github.com/pycqa/isort
+    rev: 5.8.0
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
+
+  - repo: https://github.com/psf/black
+    rev: 21.6b0
+    hooks:
+      - id: black
+
+  - repo: https://gitlab.com/pycqa/flake8
+    rev: 3.9.2
+    hooks:
+      - id: flake8
diff --git a/LICENSE b/LICENSE
@@ -1,5 +1,5 @@
  Copyright 2020-2021 RangiLyu. All rights reserved.
- 
+
                                 Apache License
                            Version 2.0, January 2004
                         http://www.apache.org/licenses/

diff --git a/README.md b/README.md
@@ -44,8 +44,8 @@ Model          |Resolution|COCO mAP |Latency(ARM 4 Threads) | FLOPS      |   Par
 :-------------:|:--------:|:-------:|:--------------------:|:----------:|:---------:|:-------:
 NanoDet-m      | 320*320 |   20.6   | **10.23ms**          | **0.72G**  | **0.95M** | **1.8MB(FP16)** &#124; **980KB(INT8)**
 NanoDet-m      | 416*416 |   23.5   | 16.44ms              | 1.2G       | **0.95M** | **1.8MB(FP16)** &#124; **980KB(INT8)**
-NanoDet-m-1.5x | 320*320 |   23.5   | 13.53ms              | 1.44G      | 2.08M     |   3.9MB(FP16) &#124; 2MB(INT8) 
-NanoDet-m-1.5x | 416*416 | **26.8** | 21.53ms              | 2.42G      | 2.08M     |   3.9MB(FP16) &#124; 2MB(INT8) 
+NanoDet-m-1.5x | 320*320 |   23.5   | 13.53ms              | 1.44G      | 2.08M     |   3.9MB(FP16) &#124; 2MB(INT8)
+NanoDet-m-1.5x | 416*416 | **26.8** | 21.53ms              | 2.42G      | 2.08M     |   3.9MB(FP16) &#124; 2MB(INT8)
 NanoDet-g      | 416*416 |   22.9   | Not Designed For ARM | 4.2G       | 3.81M     |   7.7MB(FP16) &#124; 3.6MB(INT8)
 YoloV3-Tiny    | 416*416 |   16.6   | 37.6ms               | 5.62G      | 8.86M     |   33.7MB
 YoloV4-Tiny    | 416*416 |   21.7   | 32.81ms              | 6.96G      | 6.06M     |   23.0MB
@@ -222,15 +222,15 @@ NanoDet-RepVGG        | RepVGG-A0          | 416*416  |  27.8  | 11.3G | 6.75M |
 3. **Start training**
 
    NanoDet is now using [pytorch lightning](https://github.com/PyTorchLightning/pytorch-lightning) for training.
-   
+
    For both single-GPU or multiple-GPUs, run:
-   
+
    ```shell script
    python tools/train.py CONFIG_FILE_PATH
    ```
-   
+
    For **Windows users**, if you have problems with the new lightning trainer, try to use tools/deprecated/train.py
-   
+
    <details>
    <summary>follow this...</summary>
 
@@ -245,7 +245,7 @@ NanoDet-RepVGG        | RepVGG-A0          | 416*416  |  27.8  | 11.3G | 6.75M |
     ```shell script
     python -m torch.distributed.launch --nproc_per_node=GPU_NUM --master_port 29501 tools/deprecated/train.py CONFIG_FILE_PATH
     ```
-   
+
    </details>
 
 

diff --git a/config/EfficientNet-Lite/nanodet-EfficientNet-Lite0_320.yml b/config/EfficientNet-Lite/nanodet-EfficientNet-Lite0_320.yml
@@ -48,7 +48,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: /coco/train2017
     ann_path: /coco/annotations/instances_train2017.json
     input_size: [320,320] #[w,h]
@@ -66,7 +66,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[127.0, 127.0, 127.0], [128.0, 128.0, 128.0]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: /coco/val2017
     ann_path: /coco/annotations/instances_val2017.json
     input_size: [320,320] #[w,h]

diff --git a/config/EfficientNet-Lite/nanodet-EfficientNet-Lite1_416.yml b/config/EfficientNet-Lite/nanodet-EfficientNet-Lite1_416.yml
@@ -49,7 +49,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: /coco/train2017
     ann_path: /coco/annotations/instances_train2017.json
     input_size: [416,416] #[w,h]
@@ -67,7 +67,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[127.0, 127.0, 127.0], [128.0, 128.0, 128.0]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: /coco/val2017
     ann_path: /coco/annotations/instances_val2017.json
     input_size: [416,416] #[w,h]

diff --git a/config/EfficientNet-Lite/nanodet-EfficientNet-Lite2_512.yml b/config/EfficientNet-Lite/nanodet-EfficientNet-Lite2_512.yml
@@ -49,7 +49,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: /coco/train2017
     ann_path: /coco/annotations/instances_train2017.json
     input_size: [512,512] #[w,h]
@@ -67,7 +67,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[127.0, 127.0, 127.0], [128.0, 128.0, 128.0]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: /coco/val2017
     ann_path: /coco/annotations/instances_val2017.json
     input_size: [512,512] #[w,h]

diff --git a/config/RepVGG/nanodet-RepVGG-A0_416.yml b/config/RepVGG/nanodet-RepVGG-A0_416.yml
@@ -45,7 +45,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: /coco/train2017
     ann_path: /coco/annotations/instances_train2017.json
     input_size: [416,416] #[w,h]
@@ -63,7 +63,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: /coco/val2017
     ann_path: /coco/annotations/instances_val2017.json
     input_size: [416,416] #[w,h]

diff --git a/config/Transformer/nanodet-t.yml b/config/Transformer/nanodet-t.yml
@@ -52,7 +52,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [320,320] #[w,h]
@@ -70,7 +70,7 @@ data:
       saturation: [0.8, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [320,320] #[w,h]

diff --git a/config/nanodet-g.yml b/config/nanodet-g.yml
@@ -52,7 +52,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [416,416] #[w,h]
@@ -70,7 +70,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [416,416] #[w,h]

diff --git a/config/nanodet-m-0.5x.yml b/config/nanodet-m-0.5x.yml
@@ -47,7 +47,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [320,320] #[w,h]
@@ -65,7 +65,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [320,320] #[w,h]

diff --git a/config/nanodet-m-1.5x-416.yml b/config/nanodet-m-1.5x-416.yml
@@ -47,7 +47,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [416,416] #[w,h]
@@ -65,7 +65,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [416,416] #[w,h]

diff --git a/config/nanodet-m-1.5x.yml b/config/nanodet-m-1.5x.yml
@@ -47,7 +47,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [320,320] #[w,h]
@@ -65,7 +65,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [320,320] #[w,h]

diff --git a/config/nanodet-m-416.yml b/config/nanodet-m-416.yml
@@ -47,7 +47,7 @@ model:
           loss_weight: 2.0
 data:
   train:
-    name: coco
+    name: CocoDataset
     img_path: coco/train2017
     ann_path: coco/annotations/instances_train2017.json
     input_size: [416,416] #[w,h]
@@ -65,7 +65,7 @@ data:
       saturation: [0.5, 1.2]
       normalize: [[103.53, 116.28, 123.675], [57.375, 57.12, 58.395]]
   val:
-    name: coco
+    name: CocoDataset
     img_path: coco/val2017
     ann_path: coco/annotations/instances_val2017.json
     input_size: [416,416] #[w,h]