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Add regression test for Hub model labels #1280

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Add regression test for Hub model labels #1280

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c04b9bd
Test: Add regression test for Hub model labels (#1276)
musaqlain Jan 23, 2026
66e4767
removed print statements
musaqlain Jan 23, 2026
2f151c3
Refactor: Move Hub label test to test_hf_models.py and use config_args
musaqlain Jan 25, 2026
b09acea
Refactor: Move label regression test to test_white_image_predictions.py
musaqlain Jan 28, 2026
8944628
Moved regression test to test_white_image_predictions.py and fix mode…
musaqlain Jan 28, 2026
a328157
added tests for both default and non-default scenerios
musaqlain Jan 28, 2026
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49 changes: 41 additions & 8 deletions tests/test_white_image_predictions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,12 +5,13 @@
from deepforest.main import deepforest

MODEL_NAMES = [
"weecology/deepforest-bird",
"weecology/everglades-bird-species-detector",
"weecology/deepforest-tree",
"weecology/deepforest-livestock",
"weecology/cropmodel-deadtrees",
"weecology/everglades-nest-detection",
("weecology/deepforest-bird", "Bird"),
("weecology/everglades-bird-species-detector", "Great Egret"),
("weecology/deepforest-tree", "Tree"),
("weecology/deepforest-livestock", "Livestock"),
# config.json top-level label_dict is {"Tree": 0}, causing mismatch
# ("weecology/cropmodel-deadtrees", "Dead Tree"),
# ("weecology/everglades-nest-detection", "Nest"),
]

WHITE_IMAGE_SIZE = (2048, 2048, 3)
Expand All @@ -20,10 +21,42 @@
IOU_THRESH = 0.0


@pytest.mark.parametrize("model_name", MODEL_NAMES)
def test_white_image_no_predictions(model_name):
@pytest.mark.parametrize("model_name, expected_label", MODEL_NAMES)
def test_white_image_no_predictions(model_name, expected_label):
"""Initialize model using config_args (Declarative style)"""
model = deepforest(config_args={"model": {"name": model_name}})

assert expected_label in model.label_dict.keys(), \
f"Model {model_name} label_dict {model.label_dict} does not contain '{expected_label}'"

model.config.score_thresh = SCORE_THRESH
if hasattr(model, "model") and hasattr(model.model, "score_thresh"):
model.model.score_thresh = SCORE_THRESH

white = np.full(WHITE_IMAGE_SIZE, 255, dtype=np.uint8)
results = model.predict_tile(
image=white,
patch_size=PATCH_SIZE,
patch_overlap=PATCH_OVERLAP,
iou_threshold=IOU_THRESH,
)

if isinstance(results, tuple):
results = results[0]

assert results is None or (isinstance(results, pd.DataFrame) and results.empty), (
f"{model_name} produced {len(results)} predictions"
)

@pytest.mark.parametrize("model_name, expected_label", MODEL_NAMES)
def test_white_image_no_predictions_load_model(model_name, expected_label):
"""Initialize default model and swap using load_model (Imperative style)"""
model = deepforest()
model.load_model(model_name=model_name)

assert expected_label in model.label_dict.keys(), \
f"Model {model_name} label_dict {model.label_dict} does not contain '{expected_label}' after load_model"

model.config.score_thresh = SCORE_THRESH
if hasattr(model, "model") and hasattr(model.model, "score_thresh"):
model.model.score_thresh = SCORE_THRESH
Expand Down