def create_job_from_ad_hoc(project_id, location, input_uri, output_uri):
"""Creates a job based on an ad-hoc job configuration.
Args:
project_id: The GCP project ID.
location: The location to start the job in.
input_uri: Uri of the video in the Cloud Storage bucket.
output_uri: Uri of the video output folder in the Cloud Storage bucket."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.input_uri = input_uri
job.output_uri = output_uri
job.config = transcoder_v1.types.JobConfig(
elementary_streams=[
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
), ),
),
transcoder_v1.types.ElementaryStream(
key="video-stream1",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=720,
width_pixels=1280,
bitrate_bps=2500000,
frame_rate=60,
), ),
),
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000),
),
],
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
transcoder_v1.types.MuxStream(
key="hd",
container="mp4",
elementary_streams=["video-stream1", "audio-stream0"],
),
],
)
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
def get_job(project_id, location, job_id):
"""Gets a job.
Args:
project_id: The GCP project ID.
location: The location this job is in.
job_id: The job ID."""
client = TranscoderServiceClient()
name = f"projects/{project_id}/locations/{location}/jobs/{job_id}"
response = client.get_job(name=name)
print(f"Job: {response.name}")
return response
def delete_job_template(project_id, location, template_id):
"""Deletes a job template.
Args:
project_id: The GCP project ID.
location: The location of the template.
template_id: The user-defined template ID."""
client = TranscoderServiceClient()
name = f"projects/{project_id}/locations/{location}/jobTemplates/{template_id}"
response = client.delete_job_template(name=name)
print("Deleted job template")
return response
def list_job_templates(project_id, location):
"""Lists all job templates in a location.
Args:
project_id: The GCP project ID.
location: The location of the templates."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
response = client.list_job_templates(parent=parent)
print("Job templates:")
for jobTemplate in response.job_templates:
print({jobTemplate.name})
return response
def create_job_from_preset(project_id, location, input_uri, output_uri, preset):
"""Creates a job based on a job preset.
Args:
project_id: The GCP project ID.
location: The location to start the job in.
input_uri: Uri of the video in the Cloud Storage bucket.
output_uri: Uri of the video output folder in the Cloud Storage bucket.
preset: The preset template."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.input_uri = input_uri
job.output_uri = output_uri
job.template_id = preset
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
def create_job_with_embedded_captions(
project_id,
location,
input_video_uri,
input_captions_uri,
output_uri,
):
"""Creates a job based on an ad-hoc job configuration that embeds captions in the output video.
Args:
project_id (str): The GCP project ID.
location (str): The location to start the job in.
input_video_uri (str): Uri of the input video in the Cloud Storage
bucket.
input_captions_uri (str): Uri of the input captions file in the Cloud
Storage bucket.
output_uri (str): Uri of the video output folder in the Cloud Storage
bucket."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.output_uri = output_uri
job.config = transcoder_v1.types.JobConfig(
inputs=[
transcoder_v1.types.Input(
key="input0",
uri=input_video_uri,
),
transcoder_v1.types.Input(
key="caption-input0",
uri=input_captions_uri,
),
],
edit_list=[
transcoder_v1.types.EditAtom(
key="atom0",
inputs=["input0", "caption-input0"],
),
],
elementary_streams=[
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
), ),
),
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000),
),
transcoder_v1.types.ElementaryStream(
key="cea-stream0",
# The following doesn't work because "mapping" is a reserved
# argument name in GCP python client libraries (see
# https://github.com/googleapis/proto-plus-python/blob/main/proto/message.py#L447):
#
# text_stream=transcoder_v1.types.TextStream(
# codec="cea608",
# mapping=[
# transcoder_v1.types.TextStream.TextMapping(
# atom_key="atom0",
# input_key="caption-input0",
# input_track=0,
# ),
# ],
# ),
# Use a python dictionary as a workaround:
text_stream={
"codec":
"cea608",
"mapping": [{
"atom_key": "atom0",
"input_key": "caption-input0",
"input_track": 0,
}],
},
),
],
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
transcoder_v1.types.MuxStream(
key="sd-hls",
container="ts",
elementary_streams=["video-stream0", "audio-stream0"],
),
transcoder_v1.types.MuxStream(
key="sd-dash",
container="fmp4",
elementary_streams=["video-stream0"],
),
transcoder_v1.types.MuxStream(
key="audio-dash",
container="fmp4",
elementary_streams=["audio-stream0"],
),
],
manifests=[
transcoder_v1.types.Manifest(
file_name="manifest.m3u8",
type_="HLS",
mux_streams=["sd-hls"],
),
transcoder_v1.types.Manifest(
file_name="manifest.mpd",
type_="DASH",
mux_streams=["sd-dash", "audio-dash"],
),
],
)
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
def create_job_template(project_id, location, template_id):
"""Creates a job template.
Args:
project_id: The GCP project ID.
location: The location to store this template in.
template_id: The user-defined template ID."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job_template = transcoder_v1.types.JobTemplate()
job_template.name = (
f"projects/{project_id}/locations/{location}/jobTemplates/{template_id}"
)
job_template.config = transcoder_v1.types.JobConfig(
elementary_streams=[
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
),
),
),
transcoder_v1.types.ElementaryStream(
key="video-stream1",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=720,
width_pixels=1280,
bitrate_bps=2500000,
frame_rate=60,
),
),
),
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000
),
),
],
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
transcoder_v1.types.MuxStream(
key="hd",
container="mp4",
elementary_streams=["video-stream1", "audio-stream0"],
),
],
)
response = client.create_job_template(
parent=parent, job_template=job_template, job_template_id=template_id
)
print(f"Job template: {response.name}")
return response
def create_job_with_concatenated_inputs(
project_id,
location,
input1_uri,
start_time_input1,
end_time_input1,
input2_uri,
start_time_input2,
end_time_input2,
output_uri,
):
"""Creates a job based on an ad-hoc job configuration that concatenates two input videos.
Args:
project_id (str): The GCP project ID.
location (str): The location to start the job in.
input1_uri (str): Uri of the first video in the Cloud Storage bucket.
start_time_input1 (str): Start time, in fractional seconds ending in 's'
(e.g., '0s'), relative to the first input video timeline.
end_time_input1 (str): End time, in fractional seconds ending in 's'
(e.g., '8.1s'), relative to the first input video timeline.
input2_uri (str): Uri of the second video in the Cloud Storage bucket.
start_time_input2 (str): Start time, in fractional seconds ending in 's'
(e.g., '3.5s'), relative to the second input video timeline.
end_time_input2 (str): End time, in fractional seconds ending in 's'
(e.g., '15s'), relative to the second input video timeline.
output_uri (str): Uri of the video output folder in the Cloud Storage
bucket."""
s1 = duration.Duration()
s1.FromJsonString(start_time_input1)
e1 = duration.Duration()
e1.FromJsonString(end_time_input1)
s2 = duration.Duration()
s2.FromJsonString(start_time_input2)
e2 = duration.Duration()
e2.FromJsonString(end_time_input2)
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.output_uri = output_uri
job.config = transcoder_v1.types.JobConfig(
inputs=[
transcoder_v1.types.Input(
key="input1",
uri=input1_uri,
),
transcoder_v1.types.Input(
key="input2",
uri=input2_uri,
),
],
edit_list=[
transcoder_v1.types.EditAtom(
key="atom1",
inputs=["input1"],
start_time_offset=s1,
end_time_offset=e1,
),
transcoder_v1.types.EditAtom(
key="atom2",
inputs=["input2"],
start_time_offset=s2,
end_time_offset=e2,
),
],
elementary_streams=[
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
), ),
),
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000),
),
],
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
],
)
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
def create_job_with_set_number_images_spritesheet(
project_id, location, input_uri, output_uri
):
"""Creates a job based on an ad-hoc job configuration that generates two spritesheets.
Args:
project_id: The GCP project ID.
location: The location to start the job in.
input_uri: Uri of the video in the Cloud Storage bucket.
output_uri: Uri of the video output folder in the Cloud Storage bucket."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.input_uri = input_uri
job.output_uri = output_uri
job.config = transcoder_v1.types.JobConfig(
# Create an ad-hoc job. For more information, see https://cloud.google.com/transcoder/docs/how-to/jobs#create_jobs_ad_hoc.
# See all options for the job config at https://cloud.google.com/transcoder/docs/reference/rest/v1beta1/JobConfig.
elementary_streams=[
# This section defines the output video stream.
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
),
),
),
# This section defines the output audio stream.
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000
),
),
],
# This section multiplexes the output audio and video together into a container.
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
],
# Generate two sprite sheets from the input video into the GCS bucket. For more information, see
# https://cloud.google.com/transcoder/docs/how-to/generate-spritesheet#generate_set_number_of_images.
sprite_sheets=[
# Generate a 10x10 sprite sheet with 64x32px images.
transcoder_v1.types.SpriteSheet(
file_prefix="small-sprite-sheet",
sprite_width_pixels=64,
sprite_height_pixels=32,
column_count=10,
row_count=10,
total_count=100,
),
# Generate a 10x10 sprite sheet with 128x72px images.
transcoder_v1.types.SpriteSheet(
file_prefix="large-sprite-sheet",
sprite_width_pixels=128,
sprite_height_pixels=72,
column_count=10,
row_count=10,
total_count=100,
),
],
)
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
def create_job_with_static_overlay(project_id, location, input_uri,
overlay_image_uri, output_uri):
"""Creates a job based on an ad-hoc job configuration that includes a static image overlay.
Args:
project_id: The GCP project ID.
location: The location to start the job in.
input_uri: Uri of the video in the Cloud Storage bucket.
overlay_image_uri: Uri of the JPEG image for the overlay in the Cloud Storage bucket. Must be a JPEG.
output_uri: Uri of the video output folder in the Cloud Storage bucket."""
client = TranscoderServiceClient()
parent = f"projects/{project_id}/locations/{location}"
job = transcoder_v1.types.Job()
job.input_uri = input_uri
job.output_uri = output_uri
job.config = transcoder_v1.types.JobConfig(
elementary_streams=[
transcoder_v1.types.ElementaryStream(
key="video-stream0",
video_stream=transcoder_v1.types.VideoStream(
h264=transcoder_v1.types.VideoStream.H264CodecSettings(
height_pixels=360,
width_pixels=640,
bitrate_bps=550000,
frame_rate=60,
), ),
),
transcoder_v1.types.ElementaryStream(
key="audio-stream0",
audio_stream=transcoder_v1.types.AudioStream(
codec="aac", bitrate_bps=64000),
),
],
mux_streams=[
transcoder_v1.types.MuxStream(
key="sd",
container="mp4",
elementary_streams=["video-stream0", "audio-stream0"],
),
],
overlays=[
transcoder_v1.types.Overlay(
image=transcoder_v1.types.Overlay.Image(
uri=overlay_image_uri,
resolution=transcoder_v1.types.Overlay.
NormalizedCoordinate(
x=1,
y=0.5,
),
alpha=1,
),
animations=[
transcoder_v1.types.Overlay.Animation(
animation_static=transcoder_v1.types.Overlay.
AnimationStatic(
xy=transcoder_v1.types.Overlay.
NormalizedCoordinate(
x=0,
y=0,
),
start_time_offset=duration.Duration(seconds=0, ),
), ),
transcoder_v1.types.Overlay.Animation(
animation_end=transcoder_v1.types.Overlay.AnimationEnd(
start_time_offset=duration.Duration(
seconds=10, ), ), ),
],
),
],
)
response = client.create_job(parent=parent, job=job)
print(f"Job: {response.name}")
return response
