def get_image_annotation():
setup_tensorflow()
output_dir = mkdtemp()
png_output = join(output_dir, "png")
oflow_output = join(output_dir, "oflow")
de = DataExtraction(ImageInput(
input_paths="test-data/img/*"
))
de.run_annotators([
ColorHistogramAnnotator(colorspace="luv"),
DominantColorAnnotator(),
EmbedAnnotator(embedding=EmbedFrameKerasResNet50()),
FaceAnnotator(
detector=FaceDetectMtcnn(),
embedding=FaceEmbedVgg2()
),
ObjectAnnotator(detector=ObjectDetectRetinaNet()),
PngAnnotator(output_dir=png_output, size=229),
ImgAnnotator()
])
return de, output_dir
def get_video_frame_annotation():
setup_tensorflow()
output_dir = mkdtemp()
png_output = join(output_dir, "png")
oflow_output = join(output_dir, "oflow")
de = DataExtraction(FrameInput(
input_path="test-data/video-clip.mp4", bsize=128
))
frames = [1, 3, 310] # make sure there is an empty batch: 128-255
de.run_annotators([
ColorHistogramAnnotator(frames=frames, colorspace="lab"),
DominantColorAnnotator(frames=frames),
DiffAnnotator(quantiles=[40]),
EmbedAnnotator(embedding=EmbedFrameKerasResNet50(), frames=frames),
FaceAnnotator(
detector=FaceDetectMtcnn(),
embedding=FaceEmbedVgg2(),
frames=frames
),
HOFMAnnotator(frames=frames),
ObjectAnnotator(detector=ObjectDetectRetinaNet(), frames=frames),
OpticalFlowAnnotator(output_dir=oflow_output, frames=frames),
PngAnnotator(output_dir=png_output, frames=frames),
ImgAnnotator()
])
return de, output_dir
def get_video_annotation():
setup_tensorflow()
output_dir = mkdtemp()
png_output = join(output_dir, "png")
oflow_output = join(output_dir, "oflow")
de = DataExtraction(FrameInput(
input_path="test-data/video-clip.mp4", bsize=256
))
freq = 128
de.run_annotators([
ColorHistogramAnnotator(freq=freq),
DominantColorAnnotator(freq=freq),
DiffAnnotator(quantiles=[40]),
EmbedAnnotator(embedding=EmbedFrameKerasResNet50(), freq=freq),
FaceAnnotator(
detector=FaceDetectMtcnn(),
embedding=FaceEmbedVgg2(),
freq=freq
),
HOFMAnnotator(freq=freq),
ObjectAnnotator(detector=ObjectDetectRetinaNet(), freq=freq),
OpticalFlowAnnotator(output_dir=oflow_output, freq=freq),
PngAnnotator(output_dir=png_output, freq=freq)
], max_batch=2)
return de, output_dir
def get_audio_subtitle_annotation():
setup_tensorflow()
output_dir = mkdtemp()
spec_output = join(output_dir, "spec")
tone_output = join(output_dir, "tone")
de = DataExtraction(FrameInput(
input_path="test-data/video-clip.mp4", bsize=256
), ainput="test-data/video-clip.wav", sinput="test-data/video-clip.srt")
de.run_audio_annotator()
de.run_subtitle_annotator()
breaks = [0, 20, 150, 200]
de.run_aggregator(SpectrogramAnnotator(
output_dir=spec_output, breaks=breaks
))
de.run_aggregator(SpectrogramAnnotator(
spectrogram=True, breaks=breaks, name="spec-data"
))
de.run_aggregator(PowerToneAnnotator(
output_dir=tone_output, breaks=breaks
))
return de, output_dir
def run_setup_tensorflow():
setup_tensorflow()