Updated CI/CD, Codecov, and Docker image

.codecov.yml

@@ -0,0 +1,27 @@
+codecov:
+  require_ci_to_pass: yes
+
+coverage:
+  status:
+    project:
+      default:
+        threshold: 1%
+    patch:
+      default:
+        target: 50%
+  range: "50...90"
+  round: down
+  precision: 1
+
+parsers:
+  gcov:
+    branch_detection:
+      conditional: yes
+      loop: yes
+      method: no
+      macro: no
+
+comment:
+  layout: "reach,diff,flags,files,footer"
+  behavior: default
+  require_changes: no

.dockerignore

@@ -0,0 +1,32 @@
+examples/0d4e4df2-7b69-91b1-1985-c8421f2f3253.jpg
+examples/18cef191-74ed-2b5e-55a5-f58bd3d483ff.jpg
+examples/1be4d40a-6fd0-42ce-da6c-294e45781f41.jpg
+examples/1d3c85e9-ee24-f290-e7e1-6e338f2eaebb.jpg
+examples/3e043302-af1c-75a7-4057-3a2f25c123bf.jpg
+examples/43ecc08d-502a-7a51-9d68-3e40a76439a2.jpg
+examples/479058af-e774-e6aa-a2b0-9a42dd6ff8b1.jpg
+examples/7c910b87-ae3a-f580-d431-03cd89793803.jpg
+examples/8fa04489-cd94-7d8f-7e2e-5f0fe2f7ae76.jpg
+examples/bb7b4345-b98a-c727-4c94-6090f0aa4355.jpg
+
+docs/
+tests/
+
+.DS_Store
+
+*.egg-info/
+
+.coverage
+coverage/
+
+gradio_cached_examples/
+__pycache__/
+docs/build/
+
+requirements.optional.txt
+
+scoutbot/loc/models/pytorch
+scoutbot/loc/models/onnx/scout.loc.5fbfff26.1.onnx
+scoutbot/wic/models/pytorch
+scoutbot/wic/models/onnx/scout.wic.5fbfff26.3.2.onnx
+scoutbot/wic/models/onnx/scout.wic.5fbfff26.3.1.onnx

.github/workflows/python-publish.yml

@@ -63,7 +63,7 @@ jobs:
     needs: [build_wheels, build_sdist]
     runs-on: ubuntu-latest
     # upload to PyPI on every tag starting with 'v'
-    if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v')
+    if: github.event_name == 'push'  # && startsWith(github.event.ref, 'refs/tags/v')
     steps:
       - uses: actions/download-artifact@v2
         with:

.github/workflows/testing.yml

@@ -49,13 +49,11 @@ jobs:
       - name: Run coverage
         run: |
           coverage xml html
-        env:
-          LOG_WIDTH: 120
 
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v1.2.1
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          files: ./_coverage/coverage.xml
+          files: ./coverage/coverage.xml
           env_vars: OS,PYTHON
           fail_ci_if_error: true

Dockerfile

@@ -1,14 +1,23 @@
-FROM continuumio/anaconda3:latest
+FROM nvidia/cuda:11.7.1-cudnn8-runtime-ubuntu20.04
 
 ENV GRADIO_SERVER_NAME=0.0.0.0
 
 ENV GRADIO_SERVER_PORT=7860
 
+# Install apt packages
+RUN set -ex \
+ && apt-get update \
+ && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
+        python3-dev \
+        python3-pip \
+ && rm -rf /var/cache/apt \
+ && rm -rf /var/lib/apt/lists/*
+
 WORKDIR /code
 
 COPY ./ /code
 
-RUN conda install pip \
- && pip install --no-cache-dir -r requirements.txt
+RUN pip3 install --no-cache-dir -r requirements.txt \
+ && pip3 install -e .
 
-CMD python app.py
+CMD python3 app.py

README.rst

@@ -56,14 +56,17 @@ The application can also be built into a Docker image and hosted on Docker Hub.
 
 .. code:: bash
 
+    # linux/amd64
+
+    docker login
+
     export DOCKER_BUILDKIT=1
     export DOCKER_CLI_EXPERIMENTAL=enabled
-
     docker buildx create --name multi-arch-builder --use
 
     docker buildx build \
         -t wildme/scoutbot:latest \
-        --platform linux/amd64,linux/arm64 \
+        --platform linux/arm64 \
         --push \
         .
 

requirements.txt

@@ -3,7 +3,7 @@ cryptography
 gradio
 imgaug
 numpy
-onnxruntime
+onnxruntime-gpu
 opencv-python-headless
 Pillow
 rich

scoutbot/loc/__init__.py

@@ -63,7 +63,9 @@ def pre(inputs):
 
 
 def predict(data, fill=True):
-    ort_session = ort.InferenceSession(ONNX_MODEL, providers=['CPUExecutionProvider'])
+    ort_session = ort.InferenceSession(
+        ONNX_MODEL, providers=['CUDAExecutionProvider', 'CPUExecutionProvider']
+    )
 
     preds = []
     for chunk in ut.ichunks(data, BATCH_SIZE):

scoutbot/wic/__init__.py

@@ -38,7 +38,9 @@ def pre(inputs):
 
 
 def predict(data, fill=False):
-    ort_session = ort.InferenceSession(ONNX_MODEL, providers=['CPUExecutionProvider'])
+    ort_session = ort.InferenceSession(
+        ONNX_MODEL, providers=['CUDAExecutionProvider', 'CPUExecutionProvider']
+    )
 
     preds = []
     for chunk in ut.ichunks(data, BATCH_SIZE):