def test_should_return_batches_equivalent_to_number_of_frames(self):
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
video_loader = SimpleVideoLoader(video_info)
batches = list(video_loader.load())
dummy_frames = list(self.create_dummy_frames())
self.assertEqual(len(batches), NUM_FRAMES)
self.assertEqual(dummy_frames, [batch.frames[0] for batch in batches])
def test_should_return_the_new_path_after_execution(self, mock_class):
class_instatnce = mock_class.return_value
dummy_expr = type('dummy_expr', (),
{"evaluate": lambda x=None: [True, False, True]})
# Build plan tree
video = VideoMetaInfo("dummy.avi", 10, VideoFormat.AVI)
class_instatnce.load.return_value = map(
lambda x: x,
[FrameBatch([1, 2, 3], None),
FrameBatch([4, 5, 6], None)])
storage_plan = StoragePlan(video)
seq_scan = SeqScanPlan(predicate=dummy_expr)
seq_scan.append_child(storage_plan)
# Execute the plan
executor = PlanExecutor(seq_scan)
actual = executor.execute_plan()
expected = [FrameBatch([1, 3], None), FrameBatch([4, 6], None)]
mock_class.assert_called_once()
self.assertEqual(expected, actual)
def convert(statement_list):
if len(statement_list) > 1 or len(statement_list) == 0:
print('statement list must be length 1 and it was len: {}'.format(len(statement_list)))
else:
statement = statement_list[0]
# Need to Create the table and projection
from_stuff = statement.from_table
meta1 = VideoMetaInfo(file=from_stuff.table_info.table_name, c_format=VideoFormat.MOV, fps=30)
video1 = SimpleVideoLoader(video_metadata=meta1)
t1 = TableRef(video=video1, table_info=TableInfo(table_name=from_stuff.table_info.table_name))
# Creating projection (root)
projection_output = [target.col_name for target in statement.target_list]
root = LogicalProjectionPlan(videos=[video1], column_ids=projection_output, foreign_column_ids=[])
where_stuff = statement.where_clause
print(where_stuff)
# Need to create the sigma plan
if where_stuff is not None:
# Creating a select Node
select_node = SeqScanPlan(predicate=where_stuff, column_ids=projection_output, videos=[video1], foreign_column_ids=[])
root.set_children(select_node)
select_node.parent=root
select_node.set_children([t1])
t1.parent=select_node
else:
root.set_children([t1])
t1.parent = root
return root
def test_should_return_single_batch_if_batch_size_equal_to_no_of_frames(
self):
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
video_loader = SimpleVideoLoader(video_info, batch_size=NUM_FRAMES)
dummy_frames = list(
self.create_dummy_frames(filters=[i for i in range(NUM_FRAMES)]))
batches = list(video_loader.load())
self.assertEqual(1, len(batches))
self.assertEqual(dummy_frames, list(batches[0].frames))
def test_should_return_only_few_frames_when_limit_is_specified(self):
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
limit = 4
video_loader = SimpleVideoLoader(video_info, limit=limit)
dummy_frames = list(
self.create_dummy_frames(filters=[i for i in range(limit)]))
batches = list(video_loader.load())
self.assertEqual(limit, len(batches))
self.assertEqual(dummy_frames, [batch.frames[0] for batch in batches])
def test_should_skip_first_two_frames_with_offset_two(self):
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
video_loader = SimpleVideoLoader(video_info, offset=2)
dummy_frames = list(
self.create_dummy_frames(filters=[i
for i in range(2, NUM_FRAMES)]))
batches = list(video_loader.load())
self.assertEqual(NUM_FRAMES - 2, len(batches))
self.assertEqual(dummy_frames, [batch.frames[0] for batch in batches])
def test_should_return_half_then_number_of_batches_with_skip_of_two(self):
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
video_loader = SimpleVideoLoader(video_info, skip_frames=2)
batches = list(video_loader.load())
dummy_frames = list(
self.create_dummy_frames(
filters=[i * 2 for i in range(NUM_FRAMES // 2)]))
self.assertEqual(len(batches), NUM_FRAMES / 2)
self.assertEqual(dummy_frames, [batch.frames[0] for batch in batches])
def test_calling_storage_executor_should_return_batches(self, mock_class):
class_instance = mock_class.return_value
video_info = VideoMetaInfo('dummy.avi', 10, VideoFormat.MPEG)
storage_plan = StoragePlan(video_info)
executor = DiskStorageExecutor(storage_plan)
class_instance.load.return_value = range(5)
actual = list(executor.next())
mock_class.assert_called_once_with(video_info,
batch_size=storage_plan.batch_size,
limit=storage_plan.limit,
offset=storage_plan.offset,
skip_frames=storage_plan.skip_frames
)
class_instance.load.assert_called_once()
self.assertEqual(list(range(5)), actual)
def findDataNames(self, searchDir):
"""
findDataNames enumerates all training data for the model and
returns a list of tuples where the first element is a EVA VideoMetaInfo
object and the second is a string label of
the correct video classification
Inputs:
- searchDir = path to the directory containing the video data
Outputs:
- videoFileNameList = list of tuples where each tuple corresponds
to a video in the data set.
The tuple contains the path to the video,
its label, and a nest tuple containing the shape
- labelList = a list of labels that correspond to labels in labelMap
- inverseLabelMap = an inverse mapping between the string
representation of the label name and an
integer representation of that label
"""
# Find all video files and corresponding labels in search directory
videoFileNameList = glob(searchDir + "**/*.avi", recursive=True)
random.shuffle(videoFileNameList)
labels = [split(dirname(a))[1] for a in videoFileNameList]
videoMetaList = [
VideoMetaInfo(f, 30, VideoFormat.AVI) for f in videoFileNameList
]
inverseLabelMap = {k: v for (k, v) in enumerate(list(set(labels)))}
labelMap = {v: k for (k, v) in enumerate(list(set(labels)))}
labelList = [labelMap[l] for l in labels]
return (videoMetaList, labelList, inverseLabelMap)