✅ [Pass] test for v7 structure!
Browse files- tests/conftest.py +26 -2
- tests/test_model/test_yolo.py +10 -0
- tests/test_tools/test_solver.py +11 -1
- tests/test_utils/test_bounding_box_utils.py +20 -0
tests/conftest.py
CHANGED
@@ -8,7 +8,7 @@ from hydra import compose, initialize
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project_root = Path(__file__).resolve().parent.parent
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sys.path.append(str(project_root))
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-
from yolo import Config, Vec2Box, create_model
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from yolo.model.yolo import YOLO
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from yolo.tools.data_loader import StreamDataLoader, YoloDataLoader
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from yolo.tools.dataset_preparation import prepare_dataset
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@@ -42,6 +42,11 @@ def inference_cfg():
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return get_cfg(overrides=["task=inference"])
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@pytest.fixture(scope="session")
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def device():
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return torch.device("cuda" if torch.cuda.is_available() else "cpu")
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@@ -65,12 +70,26 @@ def model(train_cfg: Config, device) -> YOLO:
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return model.to(device)
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@pytest.fixture(scope="session")
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def vec2box(train_cfg: Config, model: YOLO, device) -> Vec2Box:
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-
vec2box =
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return vec2box
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@pytest.fixture(scope="session")
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def train_dataloader(train_cfg: Config):
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prepare_dataset(train_cfg.dataset, task="train")
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@@ -88,6 +107,11 @@ def file_stream_data_loader(inference_cfg: Config):
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return StreamDataLoader(inference_cfg.task.data)
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@pytest.fixture(scope="session")
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def directory_stream_data_loader(inference_cfg: Config):
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inference_cfg.task.data.source = "tests/data/images/train"
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project_root = Path(__file__).resolve().parent.parent
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sys.path.append(str(project_root))
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+
from yolo import Anc2Box, Config, Vec2Box, create_converter, create_model
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from yolo.model.yolo import YOLO
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from yolo.tools.data_loader import StreamDataLoader, YoloDataLoader
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from yolo.tools.dataset_preparation import prepare_dataset
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return get_cfg(overrides=["task=inference"])
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+
@pytest.fixture(scope="session")
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def inference_v7_cfg():
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return get_cfg(overrides=["task=inference", "model=v7"])
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@pytest.fixture(scope="session")
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def device():
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return torch.device("cuda" if torch.cuda.is_available() else "cpu")
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return model.to(device)
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@pytest.fixture(scope="session")
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def model_v7(inference_v7_cfg: Config, device) -> YOLO:
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model = create_model(inference_v7_cfg.model)
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return model.to(device)
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@pytest.fixture(scope="session")
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def vec2box(train_cfg: Config, model: YOLO, device) -> Vec2Box:
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vec2box = create_converter(train_cfg.model.name, model, train_cfg.model.anchor, train_cfg.image_size, device)
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return vec2box
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@pytest.fixture(scope="session")
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def anc2box(inference_v7_cfg: Config, model: YOLO, device) -> Anc2Box:
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anc2box = create_converter(
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inference_v7_cfg.model.name, model, inference_v7_cfg.model.anchor, inference_v7_cfg.image_size, device
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)
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return anc2box
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@pytest.fixture(scope="session")
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def train_dataloader(train_cfg: Config):
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prepare_dataset(train_cfg.dataset, task="train")
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return StreamDataLoader(inference_cfg.task.data)
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@pytest.fixture(scope="session")
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def file_stream_data_loader_v7(inference_v7_cfg: Config):
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return StreamDataLoader(inference_v7_cfg.task.data)
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@pytest.fixture(scope="session")
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def directory_stream_data_loader(inference_cfg: Config):
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inference_cfg.task.data.source = "tests/data/images/train"
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tests/test_model/test_yolo.py
CHANGED
@@ -36,6 +36,16 @@ def test_build_model_v9m():
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assert len(model.model) == 39
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@pytest.fixture
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def cfg() -> Config:
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with initialize(config_path="../../yolo/config", version_base=None):
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assert len(model.model) == 39
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def test_build_model_v7():
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with initialize(config_path=config_path, version_base=None):
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cfg: Config = compose(config_name=config_name, overrides=[f"model=v7"])
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OmegaConf.set_struct(cfg.model, False)
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cfg.weight = None
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model = YOLO(cfg.model)
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assert len(model.model) == 106
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@pytest.fixture
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def cfg() -> Config:
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with initialize(config_path="../../yolo/config", version_base=None):
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tests/test_tools/test_solver.py
CHANGED
@@ -11,7 +11,7 @@ from yolo.config.config import Config
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from yolo.model.yolo import YOLO
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from yolo.tools.data_loader import StreamDataLoader, YoloDataLoader
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from yolo.tools.solver import ModelTester, ModelTrainer, ModelValidator
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from yolo.utils.bounding_box_utils import Vec2Box
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@pytest.fixture
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@@ -41,6 +41,12 @@ def model_tester(inference_cfg: Config, model: YOLO, vec2box: Vec2Box, validatio
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return tester
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def test_model_tester_initialization(model_tester: ModelTester):
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assert isinstance(model_tester.model, YOLO)
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assert hasattr(model_tester, "solve")
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@@ -50,6 +56,10 @@ def test_model_tester_solve_single_image(model_tester: ModelTester, file_stream_
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model_tester.solve(file_stream_data_loader)
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@pytest.fixture
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def model_trainer(train_cfg: Config, model: YOLO, vec2box: Vec2Box, train_progress_logger, device):
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train_cfg.task.epoch = 2
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from yolo.model.yolo import YOLO
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from yolo.tools.data_loader import StreamDataLoader, YoloDataLoader
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from yolo.tools.solver import ModelTester, ModelTrainer, ModelValidator
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from yolo.utils.bounding_box_utils import Anc2Box, Vec2Box
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@pytest.fixture
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return tester
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@pytest.fixture
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def modelv7_tester(inference_v7_cfg: Config, model_v7: YOLO, anc2box: Anc2Box, validation_progress_logger, device):
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tester = ModelTester(inference_v7_cfg, model_v7, anc2box, validation_progress_logger, device)
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return tester
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def test_model_tester_initialization(model_tester: ModelTester):
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assert isinstance(model_tester.model, YOLO)
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assert hasattr(model_tester, "solve")
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model_tester.solve(file_stream_data_loader)
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def test_modelv7_tester_solve_single_image(modelv7_tester: ModelTester, file_stream_data_loader_v7: StreamDataLoader):
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modelv7_tester.solve(file_stream_data_loader_v7)
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@pytest.fixture
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def model_trainer(train_cfg: Config, model: YOLO, vec2box: Vec2Box, train_progress_logger, device):
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train_cfg.task.epoch = 2
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tests/test_utils/test_bounding_box_utils.py
CHANGED
@@ -9,7 +9,9 @@ from torch import allclose, float32, isclose, tensor
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project_root = Path(__file__).resolve().parent.parent.parent
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sys.path.append(str(project_root))
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from yolo import Config, NMSConfig, create_model
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from yolo.utils.bounding_box_utils import (
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Vec2Box,
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bbox_nms,
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calculate_iou,
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@@ -125,6 +127,24 @@ def test_vec2box_autoanchor():
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assert vec2box.scaler.shape == tuple([4200])
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def test_bbox_nms():
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cls_dist = tensor(
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[[[0.1, 0.7, 0.2], [0.6, 0.3, 0.1]], [[0.4, 0.4, 0.2], [0.5, 0.4, 0.1]]] # Example class distribution
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project_root = Path(__file__).resolve().parent.parent.parent
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sys.path.append(str(project_root))
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from yolo import Config, NMSConfig, create_model
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from yolo.config.config import AnchorConfig
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from yolo.utils.bounding_box_utils import (
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Anc2Box,
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Vec2Box,
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bbox_nms,
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calculate_iou,
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assert vec2box.scaler.shape == tuple([4200])
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def test_anc2box_autoanchor(inference_v7_cfg: Config):
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model = create_model(inference_v7_cfg.model, weight_path=None).to(device)
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anchor_cfg: AnchorConfig = inference_v7_cfg.model.anchor.copy()
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del anchor_cfg.strides
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anc2box = Anc2Box(model, anchor_cfg, inference_v7_cfg.image_size, device)
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assert anc2box.strides == [8, 16, 32]
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anc2box.update((320, 640))
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anchor_grids_shape = [anchor_grid.shape for anchor_grid in anc2box.anchor_grids]
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assert anchor_grids_shape == [
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torch.Size([1, 1, 80, 80, 2]),
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torch.Size([1, 1, 40, 40, 2]),
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torch.Size([1, 1, 20, 20, 2]),
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]
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assert anc2box.anchor_scale.shape == torch.Size([3, 1, 3, 1, 1, 2])
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def test_bbox_nms():
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cls_dist = tensor(
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[[[0.1, 0.7, 0.2], [0.6, 0.3, 0.1]], [[0.4, 0.4, 0.2], [0.5, 0.4, 0.1]]] # Example class distribution
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