Better GitHub workflow (#59)

* Update tests.yml

* Renamed test images

* Corrected test

* Fixed README

* Better images names

.github/workflows/tests.yml

@@ -5,7 +5,20 @@
 
 name: Tests
 
-on: [push, pull_request]
+on:
+  push:
+    paths:
+      - 'monoloco/**'
+      - 'test/**'
+      - 'docs/test*'
+      - '.github/workflows/tests.yml'
+
+  pull_request:
+    paths:
+      - 'monoloco/**'
+      - 'test/**'
+      - 'docs/test*'
+      - '.github/workflows/tests.yml'
 
 jobs:
   build:

README.md

@@ -17,7 +17,7 @@ This library is based on three research projects for monocular/stereo 3D human l
 [T. Mordan](https://people.epfl.ch/taylor.mordan/?lang=en), [A. Alahi](https://scholar.google.com/citations?user=UIhXQ64AAAAJ&hl=en)_, ICRA 2021 <br /> 
 __[Article](https://arxiv.org/abs/2008.10913)__  &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;   __[Citation](#Citation)__  &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; __[Video](https://www.youtube.com/watch?v=pGssROjckHU)__
      
-<img src="docs/out_000840_multi.jpg" width="700"/>
+<img src="docs/out_test_000840_multi.jpg" width="700"/>
 
 ---
 
@@ -125,24 +125,24 @@ If you provide a ground-truth json file to compare the predictions of the networ
 For an example image, run the following command:
 
 ```sh
-python -m monoloco.run predict docs/002282.png \
+python -m monoloco.run predict docs/test_002282.png \
 --path_gt names-kitti-200615-1022.json \
 -o <output directory> \
 --long-edge <rescale the image by providing dimension of long side>
 --n_dropout <50 to include epistemic uncertainty, 0 otherwise>
 ```
 
-![predict](docs/out_002282.png.multi.jpg)
+![predict](docs/out_test_002282.png.multi.jpg)
 
 To show all the instances estimated by MonoLoco add the argument `--show_all` to the above command.
 
-![predict_all](docs/out_002282.png.multi_all.jpg)
+![predict_all](docs/out_test_002282.png.multi_all.jpg)
 
 It is also possible to run [openpifpaf](https://github.com/vita-epfl/openpifpaf) directly
 by using `--mode keypoints`. All the other pifpaf arguments are also supported 
 and can be checked with `python -m monoloco.run predict --help`.
 
-![predict](docs/out_002282_pifpaf.jpg)
+![predict](docs/out_test_002282_pifpaf.jpg)
 
 
 **Stereo Examples** <br /> 
@@ -161,7 +161,7 @@ python3 -m monoloco.run predict --mode stereo \
  -o data/output  -long_edge 2500
  ```
  
-![Crowded scene](docs/out_000840_multi.jpg)
+![Crowded scene](docs/out_test_000840_multi.jpg)
 
 ```sh
 python3 -m monoloco.run predict --glob docs/005523*.png \ --output_types multi \
@@ -183,7 +183,7 @@ For more info, run:
 **Examples** <br>
 An example from the Collective Activity Dataset is provided below.
 
-<img src="docs/frame0032.jpg" width="500"/>
+<img src="docs/test_frame0032.jpg" width="500"/>
 
 To visualize social distancing run the below, command:
 
@@ -192,11 +192,11 @@ pip install scipy
 ```
 
 ```sh
-python -m monoloco.run predict docs/frame0032.jpg \
+python -m monoloco.run predict docs/test_frame0032.jpg \
 --activities social_distance --output_types front bird 
 ```
 
-<img src="docs/out_frame0032_front_bird.jpg" width="700"/>
+<img src="docs/out_test_frame0032_front_bird.jpg" width="700"/>
 
 ## C) Hand-raising detection
 To detect raised hand, you can add the argument `--activities raise_hand` to the prediction command.

tests/test_train_mono.py

@@ -24,7 +24,7 @@ TRAIN_COMMAND = [
 PREDICT_COMMAND = [
     'python3', '-m', 'monoloco.run',
     'predict',
-    'docs/002282.png',
+    'docs/test_002282.png',
     '--output_types', 'multi', 'json',
     '--decoder-workers=0'  # for windows
 ]
@@ -32,7 +32,7 @@ PREDICT_COMMAND = [
 PREDICT_COMMAND_SOCIAL_DISTANCE = [
     'python3', '-m', 'monoloco.run',
     'predict',
-    'docs/frame0032.jpg',
+    'docs/test_frame0032.jpg',
     '--activities', 'social_distance',
     '--output_types', 'front', 'bird',
     '--decoder-workers=0'  # for windows'
@@ -64,8 +64,8 @@ def test_train_mono(tmp_path):
     print(' '.join(predict_cmd))
     subprocess.run(predict_cmd, check=True, capture_output=True)
     print(os.listdir(tmp_path))
-    assert 'out_002282.png.multi.png' in os.listdir(tmp_path)
-    assert 'out_002282.png.monoloco.json' in os.listdir(tmp_path)
+    assert 'out_test_002282.png.multi.png' in os.listdir(tmp_path)
+    assert 'out_test_002282.png.monoloco.json' in os.listdir(tmp_path)
 
     predict_cmd_sd = PREDICT_COMMAND_SOCIAL_DISTANCE + [
         '--model={}'.format(model),
@@ -75,5 +75,5 @@ def test_train_mono(tmp_path):
     print(' '.join(predict_cmd_sd))
     subprocess.run(predict_cmd_sd, check=True, capture_output=True)
     print(os.listdir(tmp_path))
-    assert 'out_frame0032.jpg.front.png' in os.listdir(tmp_path)
-    assert 'out_frame0032.jpg.bird.png' in os.listdir(tmp_path)
+    assert 'out_test_frame0032.jpg.front.png' in os.listdir(tmp_path)
+    assert 'out_test_frame0032.jpg.bird.png' in os.listdir(tmp_path)

tests/test_train_stereo.py

@@ -26,7 +26,7 @@ PREDICT_COMMAND = [
     'python3', '-m', 'monoloco.run',
     'predict',
     '--mode=stereo',
-    '--glob', 'docs/000840*.png',
+    '--glob', 'docs/test_000840*.png',
     '--output_types', 'multi', 'json',
     '--decoder-workers=0',  # for windows'
 ]
@@ -56,4 +56,4 @@ def test_train_stereo(tmp_path):
     print(' '.join(predict_cmd))
     subprocess.run(predict_cmd, check=True, capture_output=True)
     print(os.listdir(tmp_path))
-    assert 'out_000840.png.multi.png' in os.listdir(tmp_path)
+    assert 'out_test_000840.png.multi.png' in os.listdir(tmp_path)