# Camera encode, object detection, and display

Source: [https://docs.qualcomm.com/doc/80-70015-50/topic/camera-encode-file-detection-yolov8-overlay-display.html](https://docs.qualcomm.com/doc/80-70015-50/topic/camera-encode-file-detection-yolov8-overlay-display.html)

The **gst-camera-two-stream-encode-file-detection-display.py** script encodes the
        camera stream and saves it to a file.

The application uses a YOLOv8 TFLite model to identify the objects in a scene from a
            camera stream. The application overlays the bounding boxes over the detected objects and
            displays the results.

## Use cases

1. Ensure that you complete the [Prerequisites](https://docs.qualcomm.com/doc/80-70015-50/topic/python-sample-applications.html#python-sample-applications__section_gm5_s5j_bdc).
2. Run the camera encode and object detection
                    script:

        python3 /usr/bin/gst-camera-two-stream-encode-file-detection-display.pyCopy to clipboard

The following are the default file in the Python script:

| Files | Directory |
| :--- | :--- |
| Detection model (YOLOv8) | /opt/data/YoloV8N\_Detection\_Quantized.tflite |
| Detection labels (same for both models) | /opt/data/yolov8n.labels |

## Expected output

The output is saved at /opt/data/test.mp4.

## Pipeline flow

Figure : Pipeline for camera encode and object detection
                
                ![](data:image/png;base64,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)

| Process | Description |
| --- | --- |
| [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-70015-50/topic/qtiqmmfsrc.html) | Collects two video streams from the camera:<ul class="ul" id="camera-encode-file-detection-yolov8-overlay-display__ul_wcz_11l_bdc"><br>                                    <li class="li">One stream is saved to a file.</li><br><br>                                    <li class="li">The second stream is used for detection. It is split using<br>                                        tee and sent to the following:<ul class="ul" id="camera-encode-file-detection-yolov8-overlay-display__ul_nsj_htk_bdc"><br>                                            <li class="li">qtimetamux to retain the video stream.</li><br><br>                                            <li class="li">qtimlvconverter to convert the video stream to input<br>                                                tensors for the classification inference.</li><br><br>                                        </ul><br><br>                                    </li><br><br>                                </ul> |
| [v4l2h264enc](https://docs.qualcomm.com/doc/80-70015-50/topic/v4l2h264enc.html) | Encodes H.264 video. |
| h264parse | Parses H.264 video. |
| mp4mux | Multiplexes the video data. |
| filesink | Saves the video data to a file. |
| **Preprocessing** | **Preprocessing** |
| [qtimlvconverter](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvconverter.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_i5w_4wl_vbc"><br>                                    <li class="li">Receives the video stream on its sink pad.</li><br><br>                                    <li class="li">Performs preprocessing:<ul class="ul" id="camera-encode-file-detection-yolov8-overlay-display__ol_zdw_qwl_vbc"><br>                                            <li class="li">Color conversion</li><br><br>                                            <li class="li">Scaling down/up</li><br><br>                                            <li class="li">Normalization on the stream data when the model<br>                                                expects the floating point values as an input</li><br><br>                                        </ul><br></li><br><br>                                    <li class="li">Converts the video stream to a tensor stream on its source<br>                                            pad.<p class="p">The object detection model uses this tensor<br>                                            stream for inferencing.</p><br></li><br><br>                                </ol> |
| **Inferencing** | **Inferencing** |
| [qtimltflite](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimltflite.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_u1l_cxl_vbc"><br>                                    <li class="li">Loads the model.</li><br><br>                                    <li class="li">Modifies the graph for the chosen delegate.</li><br><br>                                    <li class="li">Receives the tensor stream on its sinkpad.</li><br><br>                                    <li class="li">Runs the inference and produces a tensor stream with the<br>                                        inference results on its source pad.</li><br><br>                                </ol> |
| **Postprocessing** | **Postprocessing** |
| [qtimlvdetection](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimlvdetection.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_ky5_grn_vbc"><br>                                    <li class="li"> Receives the inference tensors from the object detection<br>                                        model.</li><br><br>                                    <li class="li">Converts the inference tensors on its sinkpad into formats<br>                                        such as video or text that the multimedia plugins can<br>                                        process later.</li><br><br>                                    <li class="li">Applies the threshold to the chosen number of results.</li><br><br>                                    <li class="li">Loads the corresponding modules for detection models. <p class="p">In<br>                                            this use case, qtimlvdetection does the following:<br>                                            </p><ol class="ol" type="a" id="camera-encode-file-detection-yolov8-overlay-display__ol_jcd_wnk_5bc"><br>                                            <li class="li">Loads the YOLOv8 submodule.</li><br><br>                                            <li class="li">Produces results as structures of text.</li><br><br>                                            <li class="li">Sends them to the sinkpad of qtimetamux.</li><br><br>                                        </ol><br></li><br><br>                                </ol> |
| [qtimetamux](https://docs.qualcomm.com/doc/80-70015-50/topic/qtimetamux.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_ll3_x5l_vbc"><br>                                    <li class="li">Receives video stream and text stream with bounding box<br>                                        results corresponding to the video stream on its<br>                                        sinkpads.</li><br><br>                                    <li class="li">Produces GST buffers with contents of the video stream from<br>                                        its sink pad.</li><br><br>                                    <li class="li">Adds bounding boxes as GstVideoRegionOfInterest from data<br>                                        sinkpad to GST buffers meta (meta muxing) on its source<br>                                        pad.</li><br><br>                                </ol> |
| [qtioverlay](https://docs.qualcomm.com/doc/80-70015-50/topic/qtioverlay.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_wst_y5l_vbc"><br>                                    <li class="li">Receives the multiplexed stream.</li><br><br>                                    <li class="li">Overlays the bounding boxes on the VideoFrame using CL.</li><br><br>                                    <li class="li">Produces GST buffers with overlays in its source pad.</li><br><br>                                </ol> |
| **Output** | **Output** |
| [Waylandsink](https://docs.qualcomm.com/doc/80-70015-50/topic/waylandsink.html) | <ol class="ol" id="camera-encode-file-detection-yolov8-overlay-display__ol_cgt_mwl_vbc"><br>                                    <li class="li">Receives the video in its sinkpad</li><br><br>                                    <li class="li">Submits the video stream to Weston. </li><br><br>                                    <li class="li">Weston renders the video stream on a local display<br>                                        device.</li><br><br>                                </ol> |

**Parent Topic:** [Python sample applications](https://docs.qualcomm.com/doc/80-70015-50/topic/python-sample-applications.html)

Last Published: Oct 27, 2025

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