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| import hashlib
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| import os
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| import shutil
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| import tempfile
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| from pathlib import Path
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| from typing import Iterable, List, Optional, Tuple, Union
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|
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| import av
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| import strawberry
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| from app_conf import (
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| DATA_PATH,
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| DEFAULT_VIDEO_PATH,
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| MAX_UPLOAD_VIDEO_DURATION,
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| UPLOADS_PATH,
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| UPLOADS_PREFIX,
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| )
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| from data.data_types import (
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| AddPointsInput,
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| CancelPropagateInVideo,
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| CancelPropagateInVideoInput,
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| ClearPointsInFrameInput,
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| ClearPointsInVideo,
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| ClearPointsInVideoInput,
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| CloseSession,
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| CloseSessionInput,
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| RemoveObjectInput,
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| RLEMask,
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| RLEMaskForObject,
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| RLEMaskListOnFrame,
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| StartSession,
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| StartSessionInput,
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| Video,
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| )
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| from data.loader import get_video
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| from data.store import get_videos
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| from data.transcoder import get_video_metadata, transcode, VideoMetadata
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| from inference.data_types import (
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| AddPointsRequest,
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| CancelPropagateInVideoRequest,
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| CancelPropagateInVideoRequest,
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| ClearPointsInFrameRequest,
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| ClearPointsInVideoRequest,
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| CloseSessionRequest,
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| RemoveObjectRequest,
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| StartSessionRequest,
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| )
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| from inference.predictor import InferenceAPI
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| from strawberry import relay
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| from strawberry.file_uploads import Upload
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|
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| @strawberry.type
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| class Query:
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|
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| @strawberry.field
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| def default_video(self) -> Video:
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| """
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| Return the default video.
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|
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| The default video can be set with the DEFAULT_VIDEO_PATH environment
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| variable. It will return the video that matches this path. If no video
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| is found, it will return the first video.
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| """
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| all_videos = get_videos()
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|
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| for _, v in all_videos.items():
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| if v.path == DEFAULT_VIDEO_PATH:
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| return v
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|
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| return next(iter(all_videos.values()))
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|
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| @relay.connection(relay.ListConnection[Video])
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| def videos(
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| self,
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| ) -> Iterable[Video]:
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| """
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| Return all available videos.
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| """
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| all_videos = get_videos()
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| return all_videos.values()
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|
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|
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| @strawberry.type
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| class Mutation:
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|
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| @strawberry.mutation
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| def upload_video(
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| self,
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| file: Upload,
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| start_time_sec: Optional[float] = None,
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| duration_time_sec: Optional[float] = None,
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| ) -> Video:
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| """
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| Receive a video file and store it in the configured S3 bucket.
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| """
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| max_time = MAX_UPLOAD_VIDEO_DURATION
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| filepath, file_key, vm = process_video(
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| file,
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| max_time=max_time,
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| start_time_sec=start_time_sec,
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| duration_time_sec=duration_time_sec,
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| )
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| video = get_video(
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| filepath,
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| UPLOADS_PATH,
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| file_key=file_key,
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| width=vm.width,
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| height=vm.height,
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| generate_poster=False,
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| )
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| return video
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|
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| @strawberry.mutation
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| def start_session(
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| self, input: StartSessionInput, info: strawberry.Info
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| ) -> StartSession:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = StartSessionRequest(
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| type="start_session",
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| path=f"{DATA_PATH}/{input.path}",
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| )
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| response = inference_api.start_session(request=request)
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|
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| return StartSession(session_id=response.session_id)
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|
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| @strawberry.mutation
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| def close_session(
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| self, input: CloseSessionInput, info: strawberry.Info
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| ) -> CloseSession:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = CloseSessionRequest(
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| type="close_session",
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| session_id=input.session_id,
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| )
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| response = inference_api.close_session(request)
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| return CloseSession(success=response.success)
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|
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| @strawberry.mutation
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| def add_points(
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| self, input: AddPointsInput, info: strawberry.Info
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| ) -> RLEMaskListOnFrame:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = AddPointsRequest(
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| type="add_points",
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| session_id=input.session_id,
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| frame_index=input.frame_index,
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| object_id=input.object_id,
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| points=input.points,
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| labels=input.labels,
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| clear_old_points=input.clear_old_points,
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| )
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| reponse = inference_api.add_points(request)
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|
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| return RLEMaskListOnFrame(
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| frame_index=reponse.frame_index,
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| rle_mask_list=[
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| RLEMaskForObject(
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| object_id=r.object_id,
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| rle_mask=RLEMask(counts=r.mask.counts, size=r.mask.size, order="F"),
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| )
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| for r in reponse.results
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| ],
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| )
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|
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| @strawberry.mutation
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| def remove_object(
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| self, input: RemoveObjectInput, info: strawberry.Info
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| ) -> List[RLEMaskListOnFrame]:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = RemoveObjectRequest(
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| type="remove_object", session_id=input.session_id, object_id=input.object_id
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| )
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| response = inference_api.remove_object(request)
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|
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| return [
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| RLEMaskListOnFrame(
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| frame_index=res.frame_index,
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| rle_mask_list=[
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| RLEMaskForObject(
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| object_id=r.object_id,
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| rle_mask=RLEMask(
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| counts=r.mask.counts, size=r.mask.size, order="F"
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| ),
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| )
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| for r in res.results
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| ],
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| )
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| for res in response.results
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| ]
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|
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| @strawberry.mutation
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| def clear_points_in_frame(
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| self, input: ClearPointsInFrameInput, info: strawberry.Info
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| ) -> RLEMaskListOnFrame:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = ClearPointsInFrameRequest(
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| type="clear_points_in_frame",
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| session_id=input.session_id,
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| frame_index=input.frame_index,
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| object_id=input.object_id,
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| )
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| response = inference_api.clear_points_in_frame(request)
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| return RLEMaskListOnFrame(
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| frame_index=response.frame_index,
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| rle_mask_list=[
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| RLEMaskForObject(
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| object_id=r.object_id,
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| rle_mask=RLEMask(counts=r.mask.counts, size=r.mask.size, order="F"),
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| )
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| for r in response.results
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| ],
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| )
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| @strawberry.mutation
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| def clear_points_in_video(
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| self, input: ClearPointsInVideoInput, info: strawberry.Info
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| ) -> ClearPointsInVideo:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = ClearPointsInVideoRequest(
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| type="clear_points_in_video",
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| session_id=input.session_id,
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| )
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| response = inference_api.clear_points_in_video(request)
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| return ClearPointsInVideo(success=response.success)
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|
|
| @strawberry.mutation
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| def cancel_propagate_in_video(
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| self, input: CancelPropagateInVideoInput, info: strawberry.Info
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| ) -> CancelPropagateInVideo:
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| inference_api: InferenceAPI = info.context["inference_api"]
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| request = CancelPropagateInVideoRequest(
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| type="cancel_propagate_in_video",
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| session_id=input.session_id,
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| )
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| response = inference_api.cancel_propagate_in_video(request)
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| return CancelPropagateInVideo(success=response.success)
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|
|
|
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| def get_file_hash(video_path_or_file) -> str:
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| if isinstance(video_path_or_file, str):
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| with open(video_path_or_file, "rb") as in_f:
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| result = hashlib.sha256(in_f.read()).hexdigest()
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| else:
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| video_path_or_file.seek(0)
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| result = hashlib.sha256(video_path_or_file.read()).hexdigest()
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| return result
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|
|
|
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| def _get_start_sec_duration_sec(
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| start_time_sec: Union[float, None],
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| duration_time_sec: Union[float, None],
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| max_time: float,
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| ) -> Tuple[float, float]:
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| default_seek_t = int(os.environ.get("VIDEO_ENCODE_SEEK_TIME", "0"))
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| if start_time_sec is None:
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| start_time_sec = default_seek_t
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|
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| if duration_time_sec is not None:
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| duration_time_sec = min(duration_time_sec, max_time)
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| else:
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| duration_time_sec = max_time
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| return start_time_sec, duration_time_sec
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|
|
|
|
| def process_video(
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| file: Upload,
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| max_time: float,
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| start_time_sec: Optional[float] = None,
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| duration_time_sec: Optional[float] = None,
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| ) -> Tuple[Optional[str], str, str, VideoMetadata]:
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| """
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| Process file upload including video trimming and content moderation checks.
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|
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| Returns the filepath, s3_file_key, hash & video metaedata as a tuple.
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| """
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| with tempfile.TemporaryDirectory() as tempdir:
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| in_path = f"{tempdir}/in.mp4"
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| out_path = f"{tempdir}/out.mp4"
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| with open(in_path, "wb") as in_f:
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| in_f.write(file.read())
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|
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| try:
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| video_metadata = get_video_metadata(in_path)
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| except av.InvalidDataError:
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| raise Exception("not valid video file")
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|
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| if video_metadata.num_video_streams == 0:
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| raise Exception("video container does not contain a video stream")
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| if video_metadata.width is None or video_metadata.height is None:
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| raise Exception("video container does not contain width or height metadata")
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|
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| if video_metadata.duration_sec in (None, 0):
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| raise Exception("video container does time duration metadata")
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|
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| start_time_sec, duration_time_sec = _get_start_sec_duration_sec(
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| max_time=max_time,
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| start_time_sec=start_time_sec,
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| duration_time_sec=duration_time_sec,
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| )
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|
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|
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|
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| transcode(
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| in_path,
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| out_path,
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| video_metadata,
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| seek_t=start_time_sec,
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| duration_time_sec=duration_time_sec,
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| )
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|
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| os.remove(in_path)
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| out_video_metadata = get_video_metadata(out_path)
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| if out_video_metadata.num_video_frames == 0:
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| raise Exception(
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| "transcode produced empty video; check seek time or your input video"
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| )
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|
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| filepath = None
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| file_key = None
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| with open(out_path, "rb") as file_data:
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| file_hash = get_file_hash(file_data)
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| file_data.seek(0)
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| file_key = UPLOADS_PREFIX + "/" + f"{file_hash}.mp4"
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| filepath = os.path.join(UPLOADS_PATH, f"{file_hash}.mp4")
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|
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| assert filepath is not None and file_key is not None
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| shutil.move(out_path, filepath)
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|
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| return filepath, file_key, out_video_metadata
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|
|
|
|
| schema = strawberry.Schema(
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| query=Query,
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| mutation=Mutation,
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| )
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|
|