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Included checks for image sizes while running in async and roi mode

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This commit is contained in:
kinaryml 2022-10-11 22:52:18 -07:00
parent 7726205d85
commit 6771fe69e9
1 changed files with 9 additions and 7 deletions
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16
mediapipe/tasks/python/test/vision/image_classifier_test.py
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@ -477,11 +477,19 @@ class ImageClassifierTest(parameterized.TestCase):
classifier.close() classifier.close()
def test_classify_async_succeeds_with_region_of_interest(self): def test_classify_async_succeeds_with_region_of_interest(self):
# Load the test image.
test_image = _Image.create_from_file(
test_utils.get_test_data_path('multi_objects.jpg'))
# NormalizedRect around the soccer ball.
roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164,
height=0.427)
observed_timestamp_ms = -1 observed_timestamp_ms = -1
def check_result(result: _ClassificationResult, unused_output_image: _Image, def check_result(result: _ClassificationResult, output_image: _Image,
timestamp_ms: int): timestamp_ms: int):
self.assertEqual(result, _generate_soccer_ball_results(timestamp_ms)) self.assertEqual(result, _generate_soccer_ball_results(timestamp_ms))
self.assertEqual(output_image.width, test_image.width)
self.assertEqual(output_image.height, test_image.height)
self.assertLess(observed_timestamp_ms, timestamp_ms) self.assertLess(observed_timestamp_ms, timestamp_ms)
self.observed_timestamp_ms = timestamp_ms self.observed_timestamp_ms = timestamp_ms
@ -492,12 +500,6 @@ class ImageClassifierTest(parameterized.TestCase):
classifier_options=classifier_options, classifier_options=classifier_options,
result_callback=check_result) result_callback=check_result)
classifier = _ImageClassifier.create_from_options(options) classifier = _ImageClassifier.create_from_options(options)
# Load the test image.
test_image = _Image.create_from_file(
test_utils.get_test_data_path('multi_objects.jpg'))
# NormalizedRect around the soccer ball.
roi = _NormalizedRect(x_center=0.532, y_center=0.521, width=0.164,
height=0.427)
for timestamp in range(0, 300, 30): for timestamp in range(0, 300, 30):
classifier.classify_async(test_image, timestamp, roi) classifier.classify_async(test_image, timestamp, roi)
classifier.close() classifier.close()