ultralytics 8.0.233 improve Classify train augmentations (#4546)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Kayzwer <68285002+Kayzwer@users.noreply.github.com>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: andresinsitu <andres.rodriguez@ingenieriainsitu.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>

tests/test_python.py

@@ -505,6 +505,48 @@ def test_hub():
     smart_request('GET', 'http://github.com', progress=True)
 
 
+@pytest.fixture
+def image():
+    return cv2.imread(str(SOURCE))
+
+
+@pytest.mark.parametrize(
+    'auto_augment, erasing, force_color_jitter',
+    [
+        (None, 0.0, False),
+        ('randaugment', 0.5, True),
+        ('augmix', 0.2, False),
+        ('autoaugment', 0.0, True), ],
+)
+def test_classify_transforms_train(image, auto_augment, erasing, force_color_jitter):
+    import torchvision.transforms as T
+
+    from ultralytics.data.augment import classify_augmentations
+
+    transform = classify_augmentations(
+        size=224,
+        mean=(0.5, 0.5, 0.5),
+        std=(0.5, 0.5, 0.5),
+        scale=(0.08, 1.0),
+        ratio=(3.0 / 4.0, 4.0 / 3.0),
+        hflip=0.5,
+        vflip=0.5,
+        auto_augment=auto_augment,
+        hsv_h=0.015,
+        hsv_s=0.4,
+        hsv_v=0.4,
+        force_color_jitter=force_color_jitter,
+        erasing=erasing,
+        interpolation=T.InterpolationMode.BILINEAR,
+    )
+
+    transformed_image = transform(Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)))
+
+    assert transformed_image.shape == (3, 224, 224)
+    assert torch.is_tensor(transformed_image)
+    assert transformed_image.dtype == torch.float32
+
+
 @pytest.mark.slow
 @pytest.mark.skipif(not ONLINE, reason='environment is offline')
 def test_model_tune():