Qcarcam Api
| Structure | Purpose |
| :--- | :--- |
| qcarcam_hw_cfg_t | Hardware configuration: CSI lane speed, clock rate, sensor mode. |
| qcarcam_stream_cfg_t | Stream attributes: resolution, pixel format (YUV, RAW10, P010), framerate. |
| qcarcam_buffer_t | Wrapper for ION buffers containing image data and timestamp info. |
| qcarcam_metadata_t | ISP statistics, exposure, gain, white balance data (for auto functions). |
From day one, the QCarCam API adhered to three principles:
Technically, QCarCam exposed a layered API. At the lowest level, ingest endpoints accepted RTSP, SRT, or chunked uploads for intermittent mobile connections. Metadata endpoints received telemetry bursts: NMEA GPS sentences, OBD-II snapshots, and accelerometer dumps. Higher-level endpoints returned parsed events: “hard-brake at 2024-08-12T07:14:09Z,” “rear-collision probability 0.83,” or “pedestrian crossing detected — bounding box: [x,y,w,h]; confidence: 0.91.”
The Qcarcam API itself is not ASIL-certified out of the box, but Qualcomm provides a safety variant called Qcarcam Safe. For ASIL-B or ASIL-D systems: qcarcam api
For non-safety ADAS features (e.g., surround view), the standard API is sufficient.
The API uses callbacks for event notification:
typedef void (*qcarcam_frame_ready_cb)(uint32_t session_id, qcarcam_buffer_t *buf); typedef void (*qcarcam_error_cb)(uint32_t session_id, qcarcam_error_t error);
qcarcam_register_callback(session_id, QCARCAM_CB_FRAME_READY, my_frame_handler);| Structure | Purpose | | :--- |
When you dive into the QCarCam header files and documentation, you encounter a distinct vocabulary. Here are the mechanisms that make it work.
Based on internal Qualcomm benchmarks (Snapdragon SA8155P, 4x cameras @ 8MP/30fps each): Technically, QCarCam exposed a layered API
| Metric | Value | |--------|-------| | Latency (sensor to callback) | < 11 ms (no ISP tuning) | | ISP pipeline delay | 2 – 4 frames (configurable) | | CPU overhead (4 streams, NV12) | < 5% on one A76 core | | Memory bandwidth | ~2.5 GB/s per 4K30 stream |
As adoption grew, QCarCam confronted thorny questions. Who owns the footage? When should redaction be mandatory? What if a model mislabels an event and harms someone’s livelihood?
Marina set up an ethics board and built features to support consent workflows, automated redaction of faces and plates, retention policies per jurisdiction, and dispute APIs where people could annotate or contest event labels. Every contested event triggered a manual review queue with human reviewers and the original audit trail.