# Update system packagessudo apt update && sudo apt upgrade -y# Install essential build toolssudo apt install -y build-essential cmake git pkg-configsudo apt install -y nasm yasm ninja-build# Install ARM-optimized librariessudo apt install -y libaom-dev libx264-dev libx265-devsudo apt install -y libvpx-dev libopus-dev libmp3lame-dev

# Create project directorymkdir -p ~/simabit-pipeline && cd ~/simabit-pipeline# Download SimaBit SDK (replace with actual download URL)wget https://releases.sima.live/sdk/simabit-sdk-arm64.tar.gztar -xzf simabit-sdk-arm64.tar.gz# Install additional dependenciessudo apt install -y libavformat-dev libavcodec-dev libavutil-devsudo apt install -y libswscale-dev libswresample-dev

# Navigate to SDK directorycd simabit-sdk# Configure build for ARM64 optimizationcmake -B build -DCMAKE_BUILD_TYPE=Release \  -DSIMABIT_ARM_NEON=ON \  -DSIMABIT_ARM64_OPTIMIZATIONS=ON \  -DCMAKE_C_FLAGS="-march=armv8.2-a+fp16+rcpc+dotprod" \  -DCMAKE_CXX_FLAGS="-march=armv8.2-a+fp16+rcpc+dotprod"# Compile with parallel jobscmake --build build -j$(nproc)# Install system-widesudo 

#include <simabit/simabit.h>#include <stdio.h>int main() {    simabit_context_t* ctx = simabit_create_context();    if (!ctx) {        fprintf(stderr, "Failed to create SimaBit context\n");        return 1;    }        printf("SimaBit SDK version: %s\n", simabit_get_version());    printf("ARM64 optimizations: %s\n",            simabit_has_arm_optimizations() ? "enabled" : "disabled");        simabit_destroy_context(ctx);    return 0;}

gcc -o test_simabit test_simabit.c -lsimabit./test_simabit

# Install VMAF-E dependenciessudo apt install -y python3-pip python3-devpip3 install numpy scipy matplotlib# Clone and build VMAF-Egit clone https://github.com/Netflix/vmaf.gitcd vmafmake -j$(nproc)sudo make install# Verify installationvmaf --version

import subprocessimport jsonimport sysdef calculate_vmaf_e(reference_video, encoded_video, model_path):    """Calculate VMAF-E score between reference and encoded videos"""    cmd = [        'vmaf',        '--reference', reference_video,        '--distorted', encoded_video,        '--model', model_path,        '--output', '/tmp/vmaf_output.json'    ]        result = subprocess.run(cmd, capture_output=True, text=True)    if result.returncode != 0:        raise Exception(f"VMAF-E calculation failed: {result.stderr}")        with open('/tmp/vmaf_output.json', 'r') as f:        data = json.load(f)        return data['aggregate']['VMAF_score']def quality_gate(vmaf_score, threshold=85.0):    """Implement quality gating based on VMAF-E score"""    if vmaf_score >= threshold:        print(f"✓ Quality gate passed: VMAF-E {vmaf_score:.2f} >= {threshold}")        return True    else:        print(f"✗ Quality gate failed: VMAF-E {vmaf_score:.2f} < {threshold}

import osimport subprocessimport tempfilefrom pathlib import Pathimport loggingclass SimaBitPipeline:    def __init__(self, config):        self.config = config        self.logger = logging.getLogger(__name__)            def preprocess_with_simabit(self, input_video, output_video):        """Apply SimaBit AI preprocessing"""        cmd = [            'simabit_cli',            '--input', input_video,            '--output', output_video,            '--preset', self.config['simabit_preset'],            '--quality', str(self.config['quality_target'])        ]                result = subprocess.run(cmd, capture_output=True, text=True)        if result.returncode != 0:            raise Exception(f"SimaBit preprocessing failed: {result.stderr}")                    self.logger.info(f"SimaBit preprocessing completed: {output_video}")        return output_video        def encode_av1(self, input_video, output_video, bitrate):        """Encode video using SVT-AV1 with optimized settings"""        cmd = [            'ffmpeg',            '-i', input_video,            '-c:v', 'libsvtav1',            '-b:v', f'{bitrate}k',            '-preset', '6',  # Balanced speed/quality            '-svtav1-params', 'tune=0:enable-overlays=1:scd=1',            '-c:a', 'libopus',            '-b:a', '128k',            '-y', output_video        ]                result = subprocess.run(cmd, capture_output=True, text=True)        if result.returncode != 0:            raise Exception(f"AV1 encoding failed: {result.stderr}")                    self.logger.info(f"AV1 encoding completed: {output_video}")        return output_video        def process_video(self, input_path, output_path):        """Complete video processing pipeline"""        with tempfile.TemporaryDirectory() as temp_dir:            # Step 1: SimaBit preprocessing            preprocessed = os.path.join(temp_dir, 'preprocessed.mp4')            self.preprocess_with_simabit(input_path, preprocessed)                        # Step 2: AV1 encoding            encoded = os.path.join(temp_dir, 'encoded.webm')            self.encode_av1(preprocessed, encoded, self.config['target_bitrate'])                        # Step 3: Quality validation            vmaf_score = calculate_vmaf_e(input_path, encoded, 'vmaf_v0.6.1.json')            if not quality_gate(vmaf_score, self.config['quality_threshold']):                raise Exception(f"Quality gate failed: VMAF-E {vmaf_score}")                        # Step 4: Move to final output            os.rename(encoded, output_path)                    return {            'output_path': output_path,            'vmaf_score': vmaf_score,            'bitrate_savings': self.calculate_savings(input_path, output_path)        }        def calculate_savings(self, original, optimized):        """Calculate bandwidth savings percentage"""        original_size = os.path.getsize(original)        optimized_size = os.path.getsize(optimized)        savings = ((original_size - optimized_size) / original_size) * 100        return round(savings, 2)

# pipeline_config.yamlsimabit:  preset: "streaming_optimized"  quality_target: 85encoding:  target_bitrate: 2000  # kbps  codec: "libsvtav1"  preset: 6quality:  threshold: 85.0  # VMAF-E minimum score  model: "vmaf_v0.6.1.json"aws:  region: "us-west-2"  s3_bucket: "video-processing-bucket"  instance_type: "c7g.2xlarge"

import unittestimport tempfileimport osfrom pathlib import Pathclass TestSimaBitPipeline(unittest.TestCase):    def setUp(self):        self.pipeline = SimaBitPipeline({            'simabit_preset': 'fast',            'quality_target': 80,            'target_bitrate': 1500,            'quality_threshold': 75.0        })                # Create test video samples        self.test_videos = {            'simple': 'test_data/simple_content.mp4',            'complex': 'test_data/complex_content.mp4',            'animation': 'test_data/animation_content.mp4'        }        def test_simabit_preprocessing(self):        """Test SimaBit preprocessing functionality"""        with tempfile.NamedTemporaryFile(suffix='.mp4') as output:            result = self.pipeline.preprocess_with_simabit(                self.test_videos['simple'],                 output.name            )            self.assertTrue(os.path.exists(result))            self.assertGreater(os.path.getsize(result), 0)        def test_av1_encoding(self):        """Test AV1 encoding with various bitrates"""        bitrates = [1000, 2000, 4000]                for bitrate in bitrates:            with tempfile.NamedTemporaryFile(suffix='.webm') as output:                result = self.pipeline.encode_av1(                    self.test_videos['complex'],                    output.name,                    bitrate                )                self.assertTrue(os.path.exists(result))        def test_quality_gating(self):        """Test VMAF-E quality gating"""        # Test with high-quality encode (should pass)        high_quality_score = 90.5        self.assertTrue(quality_gate(high_quality_score, 85.0))                # Test with low-quality encode (should fail)        low_quality_score = 70.2        self.assertFalse(quality_gate(low_quality_score, 85.0))        def test_end_to_end_pipeline(self):        """Test complete pipeline processing"""        with tempfile.NamedTemporaryFile(suffix='.webm') as output:            result = self.pipeline.process_video(                self.test_videos['animation'],                output.name            )                        self.assertIn('output_path', result)            self.assertIn('vmaf_score', result)            self.assertIn('bitrate_savings', result)            self.assertGreaterEqual(result['vmaf_score'], 75.0)if __name__ == '__main__':    unittest.main()

# .github/workflows/pipeline-test.ymlname: SimaBit Pipeline Testson:  push:    branches: [ main, develop ]  pull_request:    branches: [ main ]jobs:  test:    runs-on: ubuntu-latest-arm64        steps:    - uses: actions/checkout@v3        - name: Setup Python      uses: actions/setup-python@v4      with:        python-version: '3.10'        architecture: 'arm64'        - name: Install dependencies      run: |        sudo apt update        sudo apt install -y build-essential cmake nasm yasm        pip install -r requirements.txt        - name: Download test videos      run: |        mkdir -p test_data        wget -O test_data/simple_content.mp4 "${{ secrets.TEST_VIDEO_SIMPLE }}"        wget -O test_data/complex_content.mp4 "${{ secrets.TEST_VIDEO_COMPLEX }}"        wget -O test_data/animation_content.mp4 "${{ secrets.TEST_VIDEO_ANIMATION }}"        - name: Compile SimaBit SDK      run: |        cd simabit-sdk        cmake -B build -DCMAKE_BUILD_TYPE=Release        cmake --build build -j$(nproc)        sudo cmake --install build        - name: Run tests      run: |        python -m pytest tests/ -v --tb=short        - name: Upload test results      uses: actions/upload-artifact@v3      if: always()      with:        name: test-results        path: test-results