Merge pull request #29 from WildMeOrg/WIC_default_udpdate

Wic default batch size update

Author: JasonWildMe

.github/workflows/testing.yml

@@ -7,15 +7,16 @@ on: push
 
 jobs:
   test:
-    runs-on: ubuntu-latest
+    # Use the same Python version used the Dockerfile
+    runs-on: ubuntu-22.04
     strategy:
       fail-fast: false
       matrix:
-        # Use the same Python version used the Dockerfile
-        python-version: [3.x]
+        # match ubuntu-22.04
+        python-version: ['3.10']
 
     env:
-      OS: ubuntu-latest
+      OS: ubuntu-22.04
       PYTHON: ${{ matrix.python-version }}
       WIC_BATCH_SIZE: 16
 
@@ -37,7 +38,7 @@ jobs:
           pip3 install -r requirements.txt
           pip3 install -r requirements.optional.txt
           pip3 install pytest pytest-cov pytest-random-order sahi[full]
-          
+
       - name: Lint with flake8
         run: |
           # stop the build if there are Python syntax errors or undefined names

docs/environment.rst

@@ -19,7 +19,7 @@ and configurations.
       The configuration setting for which machine lerning models to use with the AGG.
       Must be one of ``phase1`` or ``mvp``, or their respective aliases as ``old`` or ``new``.
       Defaults to the value of the ``CONFIG`` environment variable.
-   - ``WIC_BATCH_SIZE`` (default: 256)
+   - ``WIC_BATCH_SIZE`` (default: 160)
       The configuration setting for how many tiles to send to the GPU in a single batch during the WIC
       prediction (forward inference).  The LOC model has a fixed batch size (16 for ``phase1`` and
       32 for ``mvp``) and cannot be adjusted.  This setting can be used to control how fast the pipeline

requirements.txt

@@ -2,14 +2,14 @@ click
 codecov
 coverage
 cryptography
-dill==0.3.7
+dill==0.3.*
 gradio
 imgaug
 numpy
 onnxruntime
-opencv-python-headless==4.7.0.68
+opencv-python-headless==4.7.0.*
 Pillow
-pooch==1.8.0
+pooch==1.8.*
 rich
 sahi==0.11.12
 sphinx-click

scoutbot/wic/dataloader.py

@@ -7,7 +7,7 @@
 import torchvision
 import utool as ut
 
-BATCH_SIZE = int(os.getenv('WIC_BATCH_SIZE', 256))
+BATCH_SIZE = int(os.getenv('WIC_BATCH_SIZE', 160))
 INPUT_SIZE = 224