### DashcamHelpers.initProtobuf()

Source: https://context7.com/teslamotors/dashcam/llms.txt

Initializes the protobuf library by loading and parsing the dashcam.proto schema file.

```APIDOC
## POST /DashcamHelpers/initProtobuf

### Description
Initializes the protobuf library by loading and parsing the dashcam.proto schema file. Returns the SeiMetadata type and enum field mappings.

### Method
POST

### Endpoint
/DashcamHelpers/initProtobuf

### Parameters
#### Request Body
- **protoPath** (string) - Optional - Path to the dashcam.proto file.

### Response
#### Success Response (200)
- **SeiMetadata** (object) - Protobuf type for decoding SEI NAL units.
- **enumFields** (object) - Mapping of enum types for Gear and AutopilotState.
```

--------------------------------

### Initialize Protobuf and Handle File Inputs

Source: https://github.com/teslamotors/dashcam/blob/master/sei_explorer.html

This snippet demonstrates how to initialize the Protobuf metadata structures and handle file uploads, including drag-and-drop support and filtering for MP4 files.

```javascript
DashcamHelpers.initProtobuf().then(({ SeiMetadata, enumFields }) => {
  seiType = SeiMetadata;
  seiFields = DashcamHelpers.deriveFieldInfo(SeiMetadata, enumFields, { useLabels: true });
  seiFieldsCsv = DashcamHelpers.deriveFieldInfo(SeiMetadata, enumFields, { useSnakeCase: true });
}).catch(err => console.error('Protobuf init failed:', err));

async function handleFiles(fileList, directoryName = null) {
  const files = (Array.isArray(fileList) ? fileList : Array.from(fileList))
    .filter(f => f.name.toLowerCase().endsWith('.mp4'));
  if (!files.length) {
    alert('Please choose at least one MP4 file.');
    return;
  }
  // Logic for processing files follows...
```

--------------------------------

### Initialize Protobuf Schema

Source: https://context7.com/teslamotors/dashcam/llms.txt

Initializes the protobuf library by loading the dashcam.proto schema. It returns the SeiMetadata type and enum mappings required for decoding SEI NAL units.

```javascript
const { SeiMetadata, enumFields } = await DashcamHelpers.initProtobuf('dashcam.proto');

const proto = DashcamHelpers.getProtobuf();
if (proto) {
    const { SeiMetadata, enumFields } = proto;
}
```

--------------------------------

### Batch Export Metadata to ZIP

Source: https://context7.com/teslamotors/dashcam/llms.txt

Processes multiple MP4 files to extract SEI metadata and bundles the resulting CSV files into a single ZIP archive using JSZip.

```javascript
const zip = new JSZip();
for (const file of files) {
    const messages = mp4.extractSeiMessages(SeiMetadata);
    zip.file(file.name.replace(/\.mp4$/i, '_sei.csv'), DashcamHelpers.buildCsv(messages, fieldInfo));
}
const blob = await zip.generateAsync({ type: 'blob' });
DashcamHelpers.downloadBlob(blob, 'dashcam_sei_metadata.zip');
```

--------------------------------

### Python CLI for SEI Metadata Extraction

Source: https://github.com/teslamotors/dashcam/blob/master/index.html

A Python script to extract SEI (Supplemental Enhancement Information) data from Tesla Dashcam MP4 files. It requires the 'protobuf' library to decode the SEI data according to the dashcam.proto schema. The script takes an MP4 file as input and outputs the extracted SEI data.

```Python
import argparse
import sys

from dashcam import dashcam_pb2

def extract_sei_data(mp4_file_path):
    """Extracts SEI data from an MP4 file.

    Args:
        mp4_file_path (str): Path to the MP4 file.

    Returns:
        bytes: The extracted SEI data, or None if not found.
    """
    try:
        with open(mp4_file_path, 'rb') as f:
            # Read the entire file content
            content = f.read()

            # Look for the SEI data marker
            sei_marker = b'\x06\x01\x02\x00\x00\x00'
            marker_index = content.find(sei_marker)

            if marker_index != -1:
                # The SEI data follows the marker
                # We need to find the end of the SEI data. This is often indicated by a length prefix.
                # For simplicity, let's assume the SEI data is relatively small and directly follows the marker.
                # A more robust solution would parse the MP4 structure to find the exact SEI NAL unit.
                # This is a simplified approach and might not work for all files.
                
                # Let's try to find the start of the next NAL unit or end of file
                # This is a heuristic and might need adjustment based on actual MP4 structure
                start_of_sei = marker_index + len(sei_marker)
                
                # Attempt to find the length of the SEI data. This is often encoded.
                # In H.264/H.265, SEI NAL units have a length prefix.
                # This part is tricky without a full MP4 parser.
                
                # For demonstration, let's assume SEI data is followed by another NAL unit or EOF.
                # We'll look for the next start code (00 00 01 or 00 00 00 01) or EOF.
                next_nal_start = -1
                for i in range(start_of_sei, len(content) - 2):
                    if content[i:i+3] == b'\x00\x00\x01' or content[i:i+4] == b'\x00\x00\x00\x01':
                        next_nal_start = i
                        break
                
                if next_nal_start != -1:
                    sei_data = content[start_of_sei:next_nal_start]
                else:
                    sei_data = content[start_of_sei:]
                
                # Further processing to decode SEI data using protobuf would go here.
                # For now, we return the raw bytes found.
                return sei_data
            else:
                print("SEI marker not found.", file=sys.stderr)
                return None

    except FileNotFoundError:
        print(f"Error: File not found at {mp4_file_path}", file=sys.stderr)
        return None
    except Exception as e:
        print(f"An error occurred: {e}", file=sys.stderr)
        return None

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Extract SEI data from Tesla Dashcam MP4 files.')
    parser.add_argument('mp4_file', help='Path to the Tesla Dashcam MP4 file.')
    args = parser.parse_args()

    sei_data = extract_sei_data(args.mp4_file)

    if sei_data:
        try:
            # Initialize the SEI message object
            sei_message = dashcam_pb2.SEI() 
            # Parse the SEI data using the protobuf schema
            sei_message.ParseFromString(sei_data)
            
            # Print the decoded SEI data (example: print timestamp)
            # The exact fields depend on the dashcam.proto definition
            if hasattr(sei_message, 'timestamp'):
                print(f"Timestamp: {sei_message.timestamp}")
            else:
                print("SEI data decoded, but 'timestamp' field not found.")
                # print(sei_message) # Uncomment to print the full decoded message

        except Exception as e:
            print(f"Error parsing SEI data with protobuf: {e}", file=sys.stderr)
            print("Raw SEI data (first 100 bytes):", sei_data[:100], file=sys.stderr)
    else:
        print("No SEI data extracted.")

```

--------------------------------

### Extract Metadata via Python CLI

Source: https://context7.com/teslamotors/dashcam/llms.txt

Use the Python CLI tool to process MP4 files and output telemetry data in CSV format. Requires the protobuf library and compiled schema.

```bash
pip install protobuf
protoc --python_out=. dashcam.proto
python sei_extractor.py path/to/dashcam-video.mp4 > metadata.csv
```

--------------------------------

### Define Tesla Dashcam Metadata Schema

Source: https://context7.com/teslamotors/dashcam/llms.txt

The Protobuf schema defines the structure of the SEI metadata embedded in video frames, including vehicle dynamics, driver inputs, and GPS coordinates.

```protobuf
syntax = "proto3";

message SeiMetadata {
  uint32 version = 1;

  enum Gear {
    GEAR_PARK = 0;
    GEAR_DRIVE = 1;
    GEAR_REVERSE = 2;
    GEAR_NEUTRAL = 3;
  }
  Gear gear_state = 2;

  uint64 frame_seq_no = 3;
  float vehicle_speed_mps = 4;
  float accelerator_pedal_position = 5;
  float steering_wheel_angle = 6;
  bool blinker_on_left = 7;
  bool blinker_on_right = 8;
  bool brake_applied = 9;

  enum AutopilotState {
    NONE = 0;
    SELF_DRIVING = 1;
    AUTOSTEER = 2;
    TACC = 3;
  }
  AutopilotState autopilot_state = 10;

  double latitude_deg = 11;
  double longitude_deg = 12;
  double heading_deg = 13;
  double linear_acceleration_mps2_x = 14;
  double linear_acceleration_mps2_y = 15;
  double linear_acceleration_mps2_z = 16;
}
```

--------------------------------

### DashcamHelpers.buildCsv()

Source: https://context7.com/teslamotors/dashcam/llms.txt

Generates CSV content from an array of SEI messages using field info for headers and value formatting.

```APIDOC
## POST /DashcamHelpers/buildCsv

### Description
Generates a CSV string from an array of SEI messages using provided field information.

### Method
POST

### Endpoint
/DashcamHelpers/buildCsv

### Parameters
#### Request Body
- **messages** (array) - Required - Array of SEI message objects.
- **fieldInfo** (array) - Required - Field metadata definitions.
```

--------------------------------

### DashcamHelpers.getFilesFromDataTransfer()

Source: https://context7.com/teslamotors/dashcam/llms.txt

Extracts MP4 files from drag-and-drop DataTransfer items.

```APIDOC
## POST /DashcamHelpers/getFilesFromDataTransfer

### Description
Recursively extracts MP4 files from drag-and-drop DataTransfer items, supporting both files and directories.

### Method
POST

### Endpoint
/DashcamHelpers/getFilesFromDataTransfer

### Parameters
#### Request Body
- **items** (DataTransferItemList) - Required - The items from a drop event.
```

--------------------------------

### Responsive CSS Layout for Dashcam Viewer

Source: https://github.com/teslamotors/dashcam/blob/master/sei_explorer.html

CSS media queries used to adjust the layout of the video viewer and metadata panels for narrow or short screens.

```css
@media (max-height: 600px), (max-width: 600px) {
  .main { flex-direction: column; }
  .video-section { flex: none; }
  .video-wrap { flex: none; min-height: 200px; max-height: 40vh; }
  .meta-section { width: auto; flex: 1; min-height: 120px; }
}
```

--------------------------------

### DashcamHelpers.deriveFieldInfo()

Source: https://context7.com/teslamotors/dashcam/llms.txt

Generates field metadata from the SeiMetadata protobuf type for display or CSV export.

```APIDOC
## POST /DashcamHelpers/deriveFieldInfo

### Description
Generates field metadata from the SeiMetadata protobuf type for display or CSV export. Supports label formatting and snake_case conversion.

### Method
POST

### Endpoint
/DashcamHelpers/deriveFieldInfo

### Parameters
#### Request Body
- **SeiMetadata** (object) - Required - The protobuf type object.
- **enumFields** (object) - Required - Enum mapping object.
- **options** (object) - Required - Configuration object (e.g., { useLabels: true, useSnakeCase: true }).
```

--------------------------------

### DashcamHelpers.formatValue()

Source: https://context7.com/teslamotors/dashcam/llms.txt

Formats a metadata value for display, handling enums, booleans, and numeric precision.

```APIDOC
## POST /DashcamHelpers/formatValue

### Description
Formats a raw metadata value into a human-readable string based on its type.

### Method
POST

### Endpoint
/DashcamHelpers/formatValue

### Parameters
#### Request Body
- **value** (any) - Required - The raw value to format.
- **enumMap** (object) - Optional - Mapping for enum values.
```

--------------------------------

### Export SEI Metadata to CSV

Source: https://github.com/teslamotors/dashcam/blob/master/sei_explorer.html

Extracts SEI metadata from all frames and converts the data into a CSV file format for download. It relies on a helper function to build the CSV string and trigger a browser download.

```javascript
async function exportCsv() {
	if (!frames || !seiFieldsCsv) return;
	const messages = frames.map(f => f.sei).filter(Boolean);
	if (!messages.length) {
		alert('No SEI metadata to export.');
		return;
	}
	const filename = (currentFileName || 'dashcam').replace(/\.mp4$/i, '') + '_sei.csv';
	DashcamHelpers.downloadBlob(new Blob([DashcamHelpers.buildCsv(messages, seiFieldsCsv)], { type: 'text/csv' }), filename);
}
```

--------------------------------

### Format Metadata Values

Source: https://context7.com/teslamotors/dashcam/llms.txt

Formats raw metadata values into human-readable strings, handling enums, boolean values, and numeric precision for floats.

```javascript
DashcamHelpers.formatValue(1, enumFields.gearState);
DashcamHelpers.formatValue(15.123456);
DashcamHelpers.formatValue(true);
```

--------------------------------

### Extract Files from DataTransfer

Source: https://context7.com/teslamotors/dashcam/llms.txt

Recursively extracts MP4 files from browser drag-and-drop DataTransfer items, supporting both individual files and directory structures.

```javascript
document.ondrop = async (e) => {
    e.preventDefault();
    const items = e.dataTransfer?.items;
    if (items) {
        const { files, directoryName } = await DashcamHelpers.getFilesFromDataTransfer(items);
    }
};
```

--------------------------------

### Parse Dashcam Frames with JavaScript

Source: https://context7.com/teslamotors/dashcam/llms.txt

The DashcamMP4 class allows for parsing video frames and accessing embedded metadata directly in the browser.

```javascript
const fileBuffer = await file.arrayBuffer();
const mp4 = new DashcamMP4(fileBuffer);
const config = mp4.getConfig();
const frames = mp4.parseFrames(SeiMetadata);
const frame = frames[100];
if (frame.sei) {
    console.log(`Speed: ${frame.sei.vehicleSpeedMps * 2.237} mph`);
}
```

--------------------------------

### Extract SEI Messages via JavaScript

Source: https://context7.com/teslamotors/dashcam/llms.txt

Extract raw SEI messages from an MP4 file without full frame parsing for efficient batch metadata processing.

```javascript
const { SeiMetadata, enumFields } = await DashcamHelpers.initProtobuf('dashcam.proto');
const mp4 = new DashcamMP4(await file.arrayBuffer());
const messages = mp4.extractSeiMessages(SeiMetadata);
messages.forEach((msg, i) => {
    console.log(`Frame ${msg.frameSeqNo}: ${msg.vehicleSpeedMps.toFixed(1)} m/s`);
});
```

--------------------------------

### Derive Metadata Field Information

Source: https://context7.com/teslamotors/dashcam/llms.txt

Generates field metadata from the SeiMetadata protobuf type. Supports configuration for UI labels or snake_case naming conventions for CSV exports.

```javascript
const { SeiMetadata, enumFields } = await DashcamHelpers.initProtobuf();
const displayFields = DashcamHelpers.deriveFieldInfo(SeiMetadata, enumFields, { useLabels: true });
const csvFields = DashcamHelpers.deriveFieldInfo(SeiMetadata, enumFields, { useSnakeCase: true });
```

--------------------------------

### Generate CSV from SEI Messages

Source: https://context7.com/teslamotors/dashcam/llms.txt

Converts an array of extracted SEI messages into a CSV string using provided field information. Includes utility to download the resulting blob.

```javascript
const csvContent = DashcamHelpers.buildCsv(messages, fieldInfo);
DashcamHelpers.downloadBlob(
    new Blob([csvContent], { type: 'text/csv' }),
    'dashcam_metadata.csv'
);
```

--------------------------------

### Decode Video Frames using WebCodecs

Source: https://github.com/teslamotors/dashcam/blob/master/sei_explorer.html

Implements a frame decoding strategy that locates the nearest preceding keyframe and decodes up to the target frame. It uses the VideoDecoder API to process encoded chunks and render them onto a canvas context.

```javascript
async function decodeFrame(index) {
	decoding = true;
	try {
		let keyIdx = index;
		while (keyIdx >= 0 && !frames[keyIdx].keyframe) keyIdx--;
		if (keyIdx < 0) { showError('No preceding keyframe'); return; }
		if (decoder) try { decoder.close(); } catch { }
		let count = 0;
		const target = index - keyIdx + 1;
		const decodePromise = new Promise((resolve, reject) => {
			decoder = new VideoDecoder({
				output: frame => {
					if (++count === target) ctx.drawImage(frame, 0, 0);
					frame.close();
					if (count >= target) resolve();
				},
				error: reject
			});
			const config = mp4.getConfig();
			decoder.configure({ codec: config.codec, width: config.width, height: config.height });
			for (let i = keyIdx; i <= index; i++) decoder.decode(createChunk(frames[i]));
			decoder.flush().catch(reject);
		});
		await decodePromise;
	} catch (err) {
		if (!err.message?.includes('Aborted')) showError('Decode failed');
	} finally {
		decoding = false;
	}
}
```

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