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[SAM] fix sam slow test (#23376)

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* fix sam slow test

* oops

* fix error message
This commit is contained in:
Younes Belkada 2023-05-17 14:27:43 +02:00 committed by GitHub
parent 22a0769933
commit 3d3c7d4213
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2 changed files with 4 additions and 4 deletions
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4
src/transformers/models/sam/processing_sam.py
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@ -208,7 +208,7 @@ class SamProcessor(ProcessorMixin):
input_points = input_points.numpy().tolist() input_points = input_points.numpy().tolist()
if not isinstance(input_points, list) or not isinstance(input_points[0], list): if not isinstance(input_points, list) or not isinstance(input_points[0], list):
raise ValueError("Input points must be a list of list of floating integers.") raise ValueError("Input points must be a list of list of floating points.")
input_points = [np.array(input_point) for input_point in input_points] input_points = [np.array(input_point) for input_point in input_points]
else: else:
input_points = None input_points = None
@ -232,7 +232,7 @@ class SamProcessor(ProcessorMixin):
or not isinstance(input_boxes[0], list) or not isinstance(input_boxes[0], list)
or not isinstance(input_boxes[0][0], list) or not isinstance(input_boxes[0][0], list)
): ):
raise ValueError("Input boxes must be a list of list of list of floating integers.") raise ValueError("Input boxes must be a list of list of list of floating points.")
input_boxes = [np.array(box).astype(np.float32) for box in input_boxes] input_boxes = [np.array(box).astype(np.float32) for box in input_boxes]
else: else:
input_boxes = None input_boxes = None

4
tests/models/sam/test_modeling_sam.py
View File

@ -481,7 +481,7 @@ class SamModelIntegrationTest(unittest.TestCase):
model.eval() model.eval()
raw_image = prepare_image() raw_image = prepare_image()
input_boxes = [[650, 900, 1000, 1250]] input_boxes = [[[650, 900, 1000, 1250]]]
input_points = [[[820, 1080]]] input_points = [[[820, 1080]]]
inputs = processor( inputs = processor(
@ -541,7 +541,7 @@ class SamModelIntegrationTest(unittest.TestCase):
model.eval() model.eval()
raw_image = prepare_image() raw_image = prepare_image()
input_boxes = [[620, 900, 1000, 1255]] input_boxes = [[[620, 900, 1000, 1255]]]
input_points = [[[820, 1080]]] input_points = [[[820, 1080]]]
labels = [[0]] labels = [[0]]