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[AZ-178] Implement streaming video detection endpoint
- Added `/detect/video` endpoint for true streaming video detection, allowing inference to start as upload bytes arrive. - Introduced `run_detect_video_stream` method in the inference module to handle video processing from a file-like object. - Updated media hashing to include a new function for computing hashes directly from files with minimal I/O. - Enhanced documentation to reflect changes in video processing and API behavior. Made-with: Cursor
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Executable
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#!/bin/bash
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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PROJECT_ROOT="$(dirname "$SCRIPT_DIR")"
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if [ -f "$PROJECT_ROOT/.env" ]; then
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set -a
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source "$PROJECT_ROOT/.env"
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set +a
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fi
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REGISTRY="${REGISTRY:?REGISTRY is required}"
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IMAGE_TAG="${IMAGE_TAG:?IMAGE_TAG is required}"
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LOADER_URL="${LOADER_URL:-http://loader:8080}"
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ANNOTATIONS_URL="${ANNOTATIONS_URL:-http://annotations:8080}"
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usage() {
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echo "Usage: $0 [--help]"
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echo "Start Azaion.Detections service container."
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exit 0
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}
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for arg in "$@"; do
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case "$arg" in
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--help) usage ;;
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esac
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done
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IMAGE="${REGISTRY}/azaion/detections-cpu:${IMAGE_TAG}"
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CONTAINER_NAME="azaion-detections"
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echo "Starting $CONTAINER_NAME from $IMAGE ..."
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docker run -d \
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--name "$CONTAINER_NAME" \
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--restart unless-stopped \
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-p 8080:8080 \
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-e LOADER_URL="$LOADER_URL" \
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-e ANNOTATIONS_URL="$ANNOTATIONS_URL" \
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-v "$(pwd)/classes.json:/app/classes.json:ro" \
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--shm-size=512m \
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--memory=4g \
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"$IMAGE"
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echo "Container $CONTAINER_NAME started."
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