# Image segmentation The **gst-ai-segmentation** application allows you to divide an image into different and meaningful parts or segments and assign a label to each homogeneous segment based on the similarity of the attributes. The application uses Qualcomm Neural Processing SDK runtime, Qualcomm AI Engine direct runtime, and LiteRT for image segmentation. The following figure shows the pipeline, which receives the input from a live camera feed, file, or an RTSP stream, preprocesses the video data, runs inferences using AI hardware, and displays the segmented data on the screen. For information about the plugins used in the pipeline flow, see [Pipeline flow](https://docs.qualcomm.com/doc/80-80022-55/topic/gst-ai-segmentation.html#section-xb4-p1s-lbc). Qualcomm Open source qtivcomposer Waylandsink qtiqmmfsrc qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 rtspsrc rtph264 depay h264parse V4l2h264dec tee qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 tee filesrc qtdemux h264parse V4l2h264dec qtimlvconverter qtimltflite/qtimlsnpe/ qtimlqnn qtimlpostprocess sink_1 sink_0 File (default) Camera (optional) RTSP (optional) **Figure : gst-ai-segmentation pipeline** ## Input and output capabilities The following table summarizes the input and output capabilities supported by the sample application: | Config | Input | Input | Input | Input | Output | Output | Output | | --- | --- | --- | --- | --- | --- | --- | --- | | Config | File src | RTSP | USB camera | MIPI camera | File | Display | RTSP | | Config #1 | Yes | Yes | No | No | No | Yes | No | | Config #2 | Yes | Yes | No | Yes | No | Yes | No | | | | | | | | | | ## Sample model and label files | Runtime | Model files | Label files | | --- | --- | --- | | Qualcomm Neural Processing SDK | deeplabv3\_plus\_mobilenet.dlc | deeplabv3\_resnet50.json | | LiteRT | deeplabv3\_plus\_mobilenet\_quantized.tflite | deeplabv3\_resnet50.json | | Qualcomm AI Engine direct | deeplabv3\_plus\_mobilenet\_quantized.bin | deeplabv3\_resnet50.json | | | | | | | | | ## Run the application on the target device The sample application uses the `/etc/configs/config_segmentation.json` file to read the input parameters. To create your own config JSON file, use [config_segmentation.json](https://git.codelinaro.org/clo/le/platform/vendor/qcom-opensource/gst-plugins-qti-oss/-/blob/imsdk.lnx.2.0.0.r2-rel/gst-sample-apps/gst-ai-segmentation/config_segmentation.json?ref_type=heads) as a reference. 1. Ensure that you complete the [Prerequisites](https://docs.qualcomm.com/doc/80-80022-55/topic/download-model-and-label-files.html). 2. Update the config JSON file based on the model, input stream, and other properties. For more information, see [Config JSON field description](https://docs.qualcomm.com/doc/80-80022-55/topic/gst-ai-segmentation.html#section-ict-rdr-32c). 3. Use the following format of the `config_segmentation.json` file: { "file-path": "", "ml-framework": "", "model": "", "labels": "", "runtime": "" } Copy to clipboard An example format file for Config #2 and Config #1 is as follows: Tab Config #2 Tab Config #1 For example, run the application using LiteRT, input video file, custom model, custom label file, DSP runtime: { "file-path": "/etc/media/video.mp4", "ml-framework": "tflite", "model": "/etc/models/deeplabv3_plus_mobilenet_quantized.tflite", "labels": "/etc/labels/deeplabv3_resnet50.json", "runtime": "dsp" } Copy to clipboard For example, run the application using LiteRT, input video file, custom model, custom label file, CPU runtime: { "file-path": "/etc/media/video.mp4", "ml-framework": "tflite", "model": "/etc/models/deeplabv3_plus_mobilenet_quantized.tflite", "labels": "/etc/labels/deeplabv3_resnet50.json", "runtime": "cpu" } Copy to clipboard Note Config #1 supports only LiteRT models and the CPU runtime. 4. Run the gst-ai-segmentation application: gst-ai-segmentation --config-file=/etc/configs/config_segmentation.json Copy to clipboard 5. To display the available help options, run the following command in the SSH shell: gst-ai-segmentation -h Copy to clipboard 6. To stop the use case, use **CTRL + C**. ## Expected output The segmented data is displayed on the local display. ![../../_images/gst-ai-segmentation.png](data:image/png;base64,UklGRiwyAABXRUJQVlA4ICAyAACw+AGdASrPAyQCPwF4slM/v7+0KTQ6w/AgCWct0XvSJB8GtdOM6UqvQf0roo8R74b1A+OHaem2MRWKrz3gvezV0bHFha7eD/z0qLcB3/o9DXx//g//HmH8/P8P+J6c+0P4P/78c/+Wy7dent6yPcX///abX+TfhDf864Ngo3Tkb0EisuAWJVuNZhpSIoXoER4od/AZJ1ZXtFAXnakTwRdIR1mtBCOs1oIR1mss1qBCVGwEL7lxw0MJdQtotYoDt6tTkmOG3zfNy/raksLunibMc4dvLdPpC6wHNheNT2NiyhBhAWLQgwgLFoQYQFi0IMICxaEGEBYgOIwx72T2qhLR7GxZQgwgLFoO/2qcUv+hEfYLStTTh8M26ogSH0TphXPPbgzcdWiqjg7ubLnoCfLwpoFhTaOVQ8+OemLKJsa0wVyPb7tC19MWaeROc/SihgfEEzmQ/8g9NwCc6CfqR6T9HbWJe4TDZ92ZWqFrvCX3KsXX47MhBMUMO4s+XXenHlrTFmnkTnFz2GVc/tTkN25HpMIwgyMutskc3PTcAnOgn6kh5iy6HgDwuIpB+fHPTFmnkTnA+phappmzq3IU9gIbbofynOgF9d92v+BFgsE/UkPPcqFyT6epDOtbIl//Pf4MmE8Y7uE1fl52doWvpizTyJHNllSCyt7GYU8S3nQT9SQ8+NuokKlfl2ewtVrwf4uvu01p5E50E/RSeYxR2XMaWe2mvLln/tHaNGZRGlpxZizTyJzoJayIM+yuxnb+vG/IqCbgE50E/RGOf+ngnotBuDLvIp/QmgwpSv4VHNQzWFvnQT9SQ8+M/Srl6tBcepHz+oSVXPwOwKlO/lUPPjnpizSotNdsyPHiAqyGH/pp5E50E/fKIX4YPHATPFWN2DNN0A+B6vA7hXKHnxz0uv1DQRuEx7fINbN1/cuas5cge9YklrAxj3z456Ys08iSdGNun8om21rgLia0LX0xZp48iSW2aULia9aME86cITsKRw3fTFmnkTnBbzslUTay3/3sDjxOboWhN3+1dL0ZsOFS13U2LlRUCfqSHnxrYqD9+EiUBq0gBu9MWaeROcjMLMgzJbiIA90HvejJpbUzY4fYL4S88LkxZp5E5xcmQPnOE6mD/NfIl7H3jCpMnXF0ELwwKTeHJ06m+WLOIxt2ZfiphdF5sqtY3AJzjjpZf0BZeg7hAbWqnThHOgn6khws0Utc73vk82n391HnRShVB2zOdBP1JdddgLhe4VWS8cnj88rgtXXwUEBm6WjRggIWDCvLpNLd7TreiCBHQLzjxQKLLXZmM6gqnJDfU7vxoD92g3owEsxcNia9MNaCZXlvMvvMhYemLNPInIYnDCv0+ebvuEG8KOW5eojR0G7YdFeBoI+4DNVbD9OoNR7kvjcAnOgnw9qls4vm7B8e3S/ca47CihxD033B9lUzbd5kgZBNy14xo/+00slXb/T5iG26toQSsPovG/rAACzn8PV0V5VnWUGDUPyNAabDRNuJHtaj+1cyNMWaeROca5pci5NCX4Uj/YZW/+n58g3Pq2TiYR61F33lKNscoefHPNXrAwuCk+MTTf7tt2eyG+hAMR+6jWNk/v18QfsKfaxPsXTaofiKsBccItagVhhiOG7IZowOZOiZoSyWS5q+aIIElgyEoiUgd/JQI50E/UkOeoCm3Yd/D/7DNhRaEXmm2eqQfZaHZm8F45QS/TEmlVlx6LTFmnjp76coGKvPASYLPM3FVeYfvAO3uFucetcdXsMmjdRFJZBpzKY55NdwvavzEMQQdPYczSBhJ9+qc93BOp5ArUJXXxauHj4nLFnQL2NVWROJLKhsH9CoJDkHhMIpsf4OmZ3fVyNrQtfTFmkJJmpsnPDU8Np9hbtWhos8TA/OEaGxxnRCzFmiRNzEB1+eM/MKPQLrhurjZtJt4xvVKFiReJCYK9QN/59MFKY4UtU7dsDVc9mvvFVPY3h+VWvcWHJjnLkakH1Xy4fNWnhR8mKFnE9P1QC9XEwsm8ohO37364avJIxnz0xZp5El/mzMFTZZeE31zZg53Pzf2Ge1a9ABnL0+dno0mHjp8ftxiVyTSUMk4u7Di5KtYu8kBnEa6kfCvs7wOKP798ZpaM/rnpxBOBT6ndYXnlqRGNx3nyqebp04PK0hnPAkHEo55h56faBjMSYqEq7VbcWIW5dlDkV1jKOdBP1JDkJQZI9Wu91hh7CRwsAKx1njjdNhqxfmY7HVd9uZRBKNRziwIDg7gbb0tZz3w46iXKjroemkRUNLg+2RefnRnrRR3mt/cqtsYoG92WAhEwjad3spyvIRBmSM/IgmM79VZix6/J82S1PqNAnfXdY9gvLaDJNzUxB3bOaQCosIXZAoBP94JuATlEQKXFGxYalz0aoq23xTXmOjixM5lrwqDKTGhR0oC1IUMNuFVLzVnYjJw+DHSghDy0myno0U8j2hkTotpX8Z8IBns4zqioWimiC1iJdzG4TE5r+cn6Zxma47t2Xa+OFWiAEkcvfp3BVjbOtO12KEzfHaR4bWFRmkDOkJelRL7cplEmyW78mW/Yf/Mx5ZDJxiPA2jjvXPyd7FlOVVb4cQVCF8QrTLJXjHT1orKUeAoz0vy/TmBDqE45U4GqjjTKNefaD1FA2z/UUqpsch2RKQTpvCV2T7ILEUXCFjYZT8rMqIFnuhhZTYQR5a87HYnYVlqW0c7Qlh6UgBCJZHyCx1N0VY2VdmKyGd4tYQ0CPCZ5MXPwwQzajWiOtxvejHYGy1UTQF7OroEWh+YcQsH0kLL5SjYxXa2ZdpMCAtnudPf/i+D4WY71rDmule/D58t+ivogAsqO9Rn7uPcAE1146aDBhpopxyy5sDB40Nc0N2GmXIScZ+18qQG7eIGob5BVO8B44B5GAriLY9ciSS7sL1rgEtIizpGdLdnzQy87waE8jq/CVk3Yk6i4Su0IPjy1rBs34sNMlwu6a9zL6+AdGPS9KM1/5uv/eK20bvkSNP9pOEvKjcE1Nstmrl7cKYZxvmmToR30+/9hplaFY+Dj42K7oEfaY6yWCYRhxLXVWnpH5YzgPUfAGzRWNirR6P6J1Xa1XrbqZssRzKFEdGieDHL3LTWzDEX3sYHRzix4bOx/NSVUp1BVoy5lKHCue1hk5DlP7aqCtappV/V80GMRcM69QnXDR2TKBhmAReCu3ml3cQrEewH+nxbAduEt3OSsgTTDwM3YOjm0FsXT8GiQe3G2OiXbCWmZ9UFfWaRMqW9QTFgwgiwc+kFsUDnr+yqgkEf3OBKKyfPRJ9kFUzC5dI86Cjy3sF9c166zBSxKZnIT1aOLTrx0W9pB6nu9rLkLFheSKmyRSS+lNzWRl4M/WARFuri0eYUEwxARFsjCCjDZYX658VKW7xADqbpbyTrxBK2PHMWwD1xmSgS5FkAf2bAIbpc2wJZRVwLGS/IdOEG9vqZHBKi+y98pqyMc7rL0/a1ZsHYINREDt6XKQ32E928Ie8tzCqYrXpa3e4kjSQ7Ur9DcqsopUo6hBjMERn2Epxgz7CKL0YbfAuUGIOHawRKdhyPMYWh9WSyOpIlzIlzpFzdC2wpU+PZjp5j29Vyay6kfbGMy4KghwJhGcWD9/igLn/ZtIGCzQhhR2+W6zSl4gnSkeF49kwKtPqy3WyHVgacFasSBZtjov+nVKGHOd1n6/WkavSdD1EKrVGSgmBjylZUIuNC5IJMruxQME5413HKkYaIAzBUg907SSNywyAJSgxrz0ZgxILCgAZq7InKaQTVvPLSRorRMVB/WHKfV7G6eUpE/Obm5JcrXUizx+l7i2N99Yzt8PzTw8n8WGA7Rd4sLdXGd4tY0tP3IPWr1UJbycg6cJObBb3nqaKlGPR8cfM+ssq7Vz3Q9q01dX1judeJxo5H0oMaFH4fA9dJywncsMijxXY16JK9Zbgvp5/VH+rtAcG9I/FF5/eHfMLXq/6Qt/ARRatUYSvCpFkiPdts1CXZx5xzDerRouNwOpSqOCQorYTqj2RtxjxzOjYSVAVEBs/qInQixDCcCJotJAcW7dQTWgMXAsryA0LcSYuT6yxzKq46ARJEhWE8K6owb0mqjbOv+8hThmPdjosr0M8/GUhiBjIOjzvE5dEHChv2v1LZvcZX2scsQ49XKTa3aSBWK6KR/v7ordNQqrBk3hZoj6ayGBAhgM4zLF037XPOOq8leX/RmVmxgnu7IOfd4aeyCfjcfo7OgChsVJnTD214ptMcKL3OUKy8Gzqdkjy2QKHSXrdV4aCfR6PXQm7rKJ2lOEQmX6iSmRjfLv6bG2gtdIIVnZ01dLljNKBar3JA9rz1psrQMCeGIp039PpBRXa60SRIiAnIm5nCHASx2uoD/UGGQtYWEk5RpKTVQ7B1KTGhqUaXG/6SSpahgZIdYj8IX3aJfxahPLb4YxrRrD24Xmy/1eIBp/w45jlnuZ8UEUXa1z5MtkJmZl3cFrsmgJ75SckGwSRRxhDuduQ/rXEYCNiU86nYjS4O1EFQXkz75bSqJYW44uSoSWoeVVIkvjDYSPQKH7kEFp6EXzafHjL3/PBH48NIsNZ4laiRcUWe0h4AidWJSzHz+cLIPhql9DQmCh/VXMlVSR7kmisv5nS/WtUMnHhuEB9HQwhTMTgGEgobgY55o+/2REvj9D4RwguS5GWzgpDH6ITp76DGE6wDLpUOemAyEj7N6PDvGvCY48/1uOAJCWB8gPU4lVQlSNJz/khrP6+2Dr8CHZUIQcy+vAAJeS028A/fZ7crQH3G5kqWHFktfojieVJnZvWqNQ7IBZ7ivgKUKlwF54J1EjVBrx4wjiTYGOvd9fvOOSl9QDvOaOjAghF0YLbVvfK9/mT4AROXKAK2AKToeREINNCnfjTZkCyt3WNzw8g1IboaoghqNZrtwYNxbAYqGFzHi/RvAWQ0bRIAnvREeYvdl6WW+sWvYMA0ByC6L5M5ZlkeV2NW5l+q7aydzVOo+5tzRwNq2hiIvnhoA8Nowc638DtoHFJOShlN8hTROvNDURCC1ld6psMNGPdq3pGEZaIgx5ExM9Bp+VlJmLvfZVSxp+wd1VMA7pNKEyCt90s4G//DN+IVvK08MI6zhJ1h/USVQ/Z3RkR3nVTPakwKVAy+TEuM7IQBeG0qflEb41nLZ12VsDCndhMcEpRSqnfG/qFoa20tlw9nRy26amS4iwaP5lXXKDwQ3YH8sQZePd2ktVt9TIpQntWoo7XWJ3yo2LuGiB9Qt9payTxqcz2TOd2MLtwm80mwKK5tdwxZGYQMxsFU3XEGcVpqP0ypsec3zn67kAUWHs3aluWZMfIwfNSckOeLJypomE8oXDozs4zuzG9hst2L6c6Uo/t/c+g8ZzdJcmTNsy0bxKzNAs2lIS+nOfLskXsQAD+9QY+AzQH8nvSZ0KAa/h0FKbxIHfuuqG1k/v/GtvyVvinBIpkic+olZ88TtB8ZZmT3k7BkQxngo5cvLXFfvmiinc+YzRsAzTkHkzkHkzkHkzkHkzkHkzkHkzkHkzkHkzkHkzkHkzkHkzkjAdZhnZcmhH/vSYonnWKBA1i/I1i/I1i7YJ9Yf+fnBj1iTj4+G+sXeF7RoIn4NbNLvk7tUUa9R+sjMUTwLhS+2SSZxji2Ft5nbuVenuAcGhjVUbH8w5AAAAAAAAUEHZpDy8AAC15ohX3FWYGAtfotCDZXRttcQyWvPx95mAuWGKKFDNq4Tn2v1FgSMl1NVzylp+WaMM9gFzNSV1WMABoe5N0dBSxxOlxUukYU1gAADE0sHEXsUOICFZx4EW8nJeXPBaQAAAtF9VdfRAycS1wAAXG6D/jBd7p5HzX50uSve64zfwzE247tun5tivax7rBE5tl85Fudjq4Vi00hiLjvv84agAA43x85HhfQ0VnIuQMTKREMASo3FNBpx7pzNPxYz8rzE6D5p3UPxZ+gS+hXBFSw7cdcG/62KpA6p+FDvO5/ZV6QAAN/rvk1NPBR8JZXwLAADcHfG22aR1J9STyWpuatBIAZOuqnjdkBQMLUsgyGiN4AAGJIgcPCDphEmsfFFpZ1mVtmTxwFQmoFD8p3iGtjTXp7+UJbfJYKJgVu8kZ33pwZXQFCU8zA3AAAADanZTz+FWtFf5UoTBZAAirEpUM2tlIAWFdLWAgSxPiKlNyriPH/l39ew50vI0Z0tz2b2jADZb63W4ON2HffxpwhYhEMQEyqeaZN92UaUGM4qGd0p+OOna+1/vfE2ZZvnZw2AABFT3cnZjZ48SC3LAAAADgMkc/Y2fT4XovbZBAOW0zUj10v7rOdhmBuIqmAB8NCOr1pfSlpfoHyjpftF/LnaMopazYAND5SkTBQHZ7nM4H6UDrUpyP1UGmxdHUnpluMV1rh58KNUiAAWRhB8leZ/fm96D0DNZCRkAAcg3I1DgrV032jXth9+ZRWnn/i7fz53gAAbbzmwsSHGF1q0Xv5zAuyEHxIVY88uUaGDttUU7s7bfbCttW6BKehIcXOGHs+IAAIRqILr0ADPxv2INpJF+aFk4sxQ8NkAAxGWXMrzdqtvXJXfiax+n7M4dgaJPdqtAABe12JOiySCEc0GCBfImRvbMofJ8fqFlwpgOOpdz7SgaLn0w8eVVMWQunfYQKbkXsJxuW1NV3WEqCF3fBR6YVa9pyfN8LAARsvhOTDg2VQauqkTen7JX0h/dE6tVgAeupDyfbAQqXvw/5+JHnoHZNG+q5QzH+A2XIZSKff6EX5QAAXeyestaye1OuhW23sl604Kun0zxONoEfvKtZmZGZZGyguzQ4I2XCNeSfNCXfVoZoeoId8lPSYrQP1ac/cE6Pvwm/e8aVpg2S3Y7yKajYA7lY3NoNTy29NWs07tPjrbz0tkHaHKrPx4t1kdlw/YAFtC6TUqFS4Ayn4lmO6PyfIqiipvB4/MEWvbK4zcmLFv88mNLew0SAJpH1tSNOhO44dWydRyAAs6aNZXiIkUgHZYjF1S6cI0+9e92awhOOeXfr3ZbOSXyF0enreTYBQhBOaxPmkx2wBrUh/TTbqqhYHmyBFeMHqHpej5dHywmT98N4j8aXgbFN4ePh/YwKwqdGK9gG/gDMpGFpl2Pz0NJFxShNZg7AUpTRZnmMCwqkuw6N3W78wnyge+2UAg+ZKi5leTRw79UGQJ+hairHWnj1EabcdlysBX5AUCWxBOw3AACeux5EhCkW644s0w5zW4qORLu497pduPixlP/ZjOOHhffi8RRKBQk5fjpW5JCuwAEfyAt2Lg4281LR/+HdqtX4pY13vb3L6ynwifuhP2CH9gBQpU4hMNEsawlblt8JKHiw2Yw5VGVUperVoDDZIyskAZ3HQArVpYRhrogPlGxCjefiAT4ks9NMzCPdA479rMKRBUBRtl7Y2LJLUw9w6OemI28OsrImCVkLg9COp7wYIfiANhJSEE/Fi8vEY/x7JA2XyxClpPJwsrl7zwt2/93ISeUbpsQEDDicrDGGQGZ+guUT4Wptd1xyOi0rCPIAajnS05f5vnrAOB8GUDWxtb+9fFTYHtP03MqdTl/k5n9H++6gN2g5MDE6vFuWZcZ+YzP/Ns5ORD64f+idfXxv9me/munI+sudl80v+TqI54pmp0fdle3fISpVfRGhEFMccMbkPVRSvmXLe5gV+mwgw1u9miZIaJYHsn708Qu0uSkLL43Cr9kXREoGjWUxK8k6EDxbHiAuXIgVGNfQAQeqqyK8ZVHtcLKYkPui1yse7uOss6iFPaSotcG0gpmqa/k19APFJn7gQAgFiQn9glhqAdvPz9Yhf2qXQLvN3xyy5ovJBhEI9ONayak/anRzg66tT1gtI/xnXPjmGFpls+m2fAfENX9ue3qNGMC5pGw0coK2WL7IiUC9/CJb1sUHdB5HFwT3gqQItu2Kavau9XCBWTexZqI1P5EiJcftteJSq5kg8+wC0XwdgXlPZkaJaKLfwvqe6EJdDXiGfjPuqowHqj0Sql1O7z+c2fWaX8PU3PjuDY+I5aQjcjeLqAAGgW0fnMu/bBNtxVTvPy7CD9VtfP0uMbNaz8aZxEavt0dIONTGk1FvDp+Tt3B04/F6zSknIUzHYA7X5sUxtP7b2TBq4p3nv/hxhde3vwvljwfxFnTWpByhOkwYTt74KhtltZNmt6R5shc4IvGEmgBVlE3tNV8FdB7D/qbS4M4bysdBelrlSCK09qBGPH24uY6w5KaUewMM3nLGXzRhGaO0J141uERR5Ee9U/Jl8vdtxXTa24Tis43Yfufa5hMKXYqNoSZm8w2KNki5LJy1PA6QEUh+8xJ1Lc5mCWacNxBACwpBUkpKTAAATliAzTqgIiNeT1s1E1U3taGAsQajDYG7RSC/9gl2//WS8ILCzJzu8hX9GkwJ3sBYoCFYwVbd3keDQQALOoWGqd5D6ODUqa1rV1nLiXGCF60J938+y+SWYGR+Kud6NHiRe20ldjeRKqwzeg3isOw+efEkVM7wFXtvKOVC1sfSkj/I00s2zkA1ZkHyV8fYHqUNCLX6zEy9T8SOgCPTNVWh9dtcYmU4aS6iAwSpet6RBL0AWCQ8vi+sB6ftZCzBZwuvlPlrJkSIlgIBNX0t2fdjemCTzzpZ5eobtQSGTqrV7QxLXFjLAAAeIlZcw0I7N+JV7x83+Vo0yEcpoG/RVJbc1+Z80YukzboRGpLaseR+TH9WBh/YXVLdoi6duTwRYGgeEIhYwBZui9X3qJaxoFOT5nBLQ0akjPrICiHeB4NHcxQjnqc/CuGC4K4a5OBk+H9tgHjVO+vdxwwG2JWwH5P6foCtkp+vkF+0gWRDCAaTRLNanKq9EnEmeyTb558GAzqMPCyDnbOzFRDthI3FQu1EvebaGuest22TTj1oK+iMDXO3xwc2bQuDOOmLZJYb6iiTpjzE6AeeRqG1H6B6P2TotMNaAHQHyEOAkIhG1iWrqDVDaQoEG0aAAU0vcLEtJfVWpcsh4xABOfVRR8E5h0Uzc/XBXreCQ0jAet+K0Y6r3z3GgEYweUOq46v0nWgq7ucxdxUQQxF8xrM6CZzy5Hhcn8V/bxZ496aTFcwItSUUzzQUgr3PgKq5bvNjvYqGzviq2i/Pb+2XPmLjFZBcVZMCeOPyh/EHRGsS63IdTSTjsZzZ4Fjnwhra8VbjVWhr0JTo1T3suURsT2bRsk3qS0mJaqRnlNSH/ve9FfLP8tVaTZnwT4MEpeqO97HPRvwE4J8d2jNqXBd8c0D9YRQZJZxSIO6eMB8iq/UC2ndeaRNAa504XD2bNr5erXSwP/vqoIAyNKpsxQTflNxlvsJcL1MOG83vdlBtWfHBs0EGEmZ0tqZE4pfFQO4AcMjVhgYvFvwLjNIDJFBF09HDdZ5XKbANgbWlyhyMeksB3REbHf/uk27p+vQKC8i5fZD5+mc3naiZMp3tb/LnLvKNfX8rFK/Ksh6sfHZWBeNz+j1eVZQ0+uMZeZN87TpRXXMP5tl5oJGyaVDt5WSFXdLHezAeR6exHNsPreloCsgtufenisfAsu1MiIs+MwtfP2rIw8jHQmCQBK2SJQL+QBy+qDvRZLuOm5a49Jm8e33uw5RG4s3gC7ZfFdI2+MkIv3OKRT+tgiTDkaJzLW9VlPsMfYyWJQugbz9/yfBxbvACYsoV1vGhcobNAzyiyCe4oaiPUiyZbAXOix45W9hXJETQRqkF0Jif0t20QgbxytM4Qh4hduolzXXTKUZI9VgLBruY6QFTwnckF/t/KKhgjhfOEyvjGLNvatuDXGkeFg60XNSPvTbOJe9q00gIxwD7b0i8Pw+jsDQwZwGQTO/jSzYOu+0LD+lxEBE5pzjBtnTcCIRKD9gYrp0vrS2idUpus79q4CtKg6MPmeewAV+yawoySQ2V6qMMcLZo6KpDCeiqE7CfDc/L/C4eK2vvurxkOqVuzHJ1vf/qM66lzPfo1VAEWLC2GBtUqNQtJiqhF01mllv3Q0KbhULvbLb3Pw6PLSjNuMKG8rk0Fj9nLlAocSaqU/ph10Ja+3SS0elmuB3UwaHua6Sk6YaEXo8IIF+ggMCixlApd+K0la4hqE5pJ4nRrUIb4B4QEMXIvsZumLjpoeIx5tuYJLcwfNf89rIw9LVEDSFumBsQbTgiIwKlcSLyEtC+YIJMK8+DinR2z3MPzWJFF+aQwgXfK6PWRgsrTVMTp40JkPuMY7pz68dIJiRJnSK+i8WQ9UUfJcLWUNiGEh23G9S5UnBCjBU2oCcPp7in8qjTeKW+VVAy59+0tNR21nSqh+1qQsawcSfamGabtyQLYdFXt/VY6PTiaPce3dC8kGdieE3dEfcdXRXEqs3JoEgj9pcVic/dPZ/XoTdYyJOtM0n4zyng27AKRAR5XdsGGj1OYRDNAvYLkEDwAoCHNmtDs5idzvXu4WT/mBXfRaDpjL5OFpH0pjP7DPEneePz8zEsF1MkrxX4BxxhRYgbfdB7ymOy4RF5AyaxeHIUHic8Z8UP77EOePKtjNKMolCcOxGXphNFOBfV6pGikZlD9D2dMhw1MB8MGlOjl4IKlWnV9Ms0hfp2bbqIz2AdqhhL8Phx78tYK8i7QLGbdxk0Y3n+FiMAQs+/zVmZu9vo72PIAZNnwdJ3iwg4uG5iv2MiHrJq2ITLUWrZNj8wWITA0/OJqlCji3xK81TRAHupLJEKD3rtBAtEckYDtZ1CRUGiflTqckSmG5uz2W59by7dZyvTrnGV8iMT6LKXKzG+LAqKKaNachJZIxJjWML0KUniEo0uzxta80etUVg6yWahu58m+mdAtSJbm3VEKnMPcgDj+c0UlzZkcWhSqksZAOIUsamOVvcjdKkr7ci+YkwrfAwe/QyZMGV5qvBzXuY4X3oUcyVJaq4YjrQLwVHz3EHxTwtLKgXnCUOMx+ECqT3sOw+mcXnfJlzoUAuaWZwI0FBQvzobe6jKXcXVtR36GZXmmwyo1gwlrjGoACddzovOhlYtYvAzx4elia0sZI6xP/1WRb47+YZjAxPf7ADyX/ZhOfZuQHTJV2Bz0p8xPqNXr5VLeobHuPxOUPveNZmzZshvnbNjjaKjUHcnEvwkB3fN2D0Rzm92oGG8vRpCUjm0FViaARCKa4cTFvSVFJ/R5x6LOp/FQvBUShE4PUL6gSd/i765TRtUKl0CUxoxElDnisZKMMU0O1vfHbXTWOHTtB5FcNrrLG5NlzSDwM/geonr3uyz0wLbmP9vlEy2zsxHSvjJVltbg0BfZkrcxsogYI+CDLO0Ml64p4+H/039oCDTLYnUhjPFgBr7wX4gFMmeIifuR5bQqp4MBLKVgCPLkizo0SHkLy7D1u4woUOFTZYaIm8oyDoqxW+yYjtA/Vc30K4LA7Tj5Qi+/q6SR34owqbIr6dtiefzmQQCqfz5I0sNc1/R1Mu/Mmp80vgf80nxdmszkNiYYH6BdA8NsHYoFw3hiMiHxAqzieFdk0zDAqpwiFNOWPZRs2aRtoetVM4Hrqja77expae92/7gGNIGqxD8n9hxVLl1M/wnaXFqeKwcGpK4hlyEhBocc0qeUS1XaTiv1kU1cp1R9ezTYtw/YXab6FqqjiPjKlLaFBOjPhb0ATTURNidoa51S/CHbhUltDXpM7Wsd/AibkoAzvgLSlYtJwkkP/13UlEiecyor4M/kfXXQ3hm7Edcmm/k2iMjsyCi7825Ornbbam7XWAIujUYMTRfGY6C+yICKmxZ1GLIBqve2iw9fAPuAsusGmXkKAvlcXlLyBDvsW9p4EjRCDDD/8494VHJkyzNqYUttgluhUoNMV/MrCC4miKjrc1KCtHnv0EXK6Wa4Yuj7PBLOw2w9s95ljCMxrN331h2+EoDIOrUkhhp7FuQ/eSINBP3H5BWMwVRP8fPeFQoX4iazSFSU2I84nBhL+jzYRqkaT+ILFfZ+AkQBaoe/VYZj4MQ8dSms7yzkMCpXPNPIRhUntlGmmvbCdZqku6Qd4p2W4sYHXWa2VZzYeJC5AA5xJe/4mSooi8PXv0ETsZsI9x1oljO3MQMiJuxyegdO30Y/k1KgEiDXZRd4VpAWQyXlK08WrWLE2aIsf4qcWHW22KqllNnxO7WhJQ91grkpY0yyt1rFutDh/068FiYHwI9P5tn9LbY1oONDVm3DWX6lHBy+sDPbAo2s8Hy8/WAST5fVbiK+WuHcCwPpe25aGOjIl8YcUhFv+xDKR+xLx7ZDjviLHCLubSpX09V04Q1xLrzVu1srMrjzrl6hCYHzeMcmMs1gZoKADPUcFee7/9Y30H0RADJiVYcBXgjuGqBFU7aBaSf3pZuLbQzWJeZmRICZx0GzY9IQ0uy6jKRfFyVYzLH+CFaegfk71WDiD3BJy00eCrBJPdDjzNT9kWE5oThcOvBOno5o1n9L9OHeOFZ4MsUgvKqlyG6OEdgLwnM1DRJLsonriT1mmcpiQNqVWfUxQZDVHpX1GGKyOA/EJAAFE52xsLuMXeKBqM6aETsksEQoDg0sPaShhHB2zJJwDRs+FZLJ2xY2yWNa1WN6ddKzR77koBl3/k8G0RxnfDvnxGwhCVvQMF//+XGzxgbLytweZj5Q6+R2PLihJ2d7HEecSHFynFysM8OvCC263DnO5WdnVupGjGkuX3n+4c/fIIP2mUSOq/XUd6j3X3YyMoFv2buvHigYBc0Z459riWdxn0gStQVMGZqAs9tqhEWcuH9Tey5k+4HKAZfsRfPDW237w/v60fd57g1aeKEFxpshiCEIb0dIeKoOEsa01jItmxb6VMnBHW24Jaf4/NcgWpC1pyfk2nx0clWgkz9QxKaqzeVF5I6otPg3GL0hVajHRllrX4zAPapsDEa79ASo8TeU+bgG+Y7k6FYgh14PkVq+Ijzw+K6gcTE6tybJO6ymRDrTnAh6GHL3XPe1GJZ3jHVcj4iux7yAczYjob35hjlb19Sut84hI1DpDocnVM9Rh0faIqP5Qr0tCg9jzTfM/0jSVYBhCbOkEe4Nyue6wsBtaey30e5rramBiKAsNELbybhVyMkP0ZDJuq4ZvE8STpHjgOJ1QzoahgTV1yvDFw94vh/ti7qQw9IErIDtZtJXXWWLzRjja0Vm+K4asaQgkOabsFysYbweFL+msrxZhrcj6IKZGqJgQpgW6sCbpNh03WByxq4L7tOxYCipKEWbhWOQa6RQFj4QTorYcyXQTJYbFLqHjBsCqXRQ1xvksH41xO3WNYmGXJY5o6kfUjTJ2kTQ86jEDenZTiN2wrwjYfbBOqZ4ZpzunXhAGALgFa/qQ6n1fRQcGbAazfHGHOErfv4u32m+t4LDF5y4a4mM3jycGmfay6LiwvWpbmJU0MV2S3k4rIsTlMKJS+3lpy2d8WPv4O49CKhDjfEHouVHvIxJC6+4q8Uc6yh5pWOHgWQNosvJWfaE5SCdevsSiqiIXU+DdEASO7j1O9Cij3h0c6SfqXS/EIc4lUzt7aQndxmesJ5nqfBqr+ZhEpEUJGKDToYmsMPUKG9/rTk5bWHN+dtR4qHJVGnZRCNolZo9qbkGdFLLgAhfkMsqOOmBZM26xcSbSZwz3F/2mwIbimzXHW/8mL0RhGKQQ59O0Eobq21fM1KKAG1xuDYRHpnR+ebLDrEo99JYWJPo0klNta7VwBbsMF8h972whEZpbN+lEGPZ+py74Ne+3+lIOCkgs7B0WaZ2JWh0mNM9XoqzbQ++N+Z5GYvYCBgwZYB0DS7Iw92DjVOfF1ItpQoG+pt8//BCak0bkflm1p6vXayoc9gb67l4RCsjGyWO/j8qREKXHbPigM2r2JCZBeskp/olWONobQKM5cKw2Bu3zKjSiECBluz43D176oVrNzVPXjkshaEiKvmWwaiJMpZKoLw2rA/1wgGFOwNkoGtf69hMQl3aAL19UlGc/CNb4DD6x4iIIXhaRx6PXWV6anhdDrNqWDlpNzuT/OIBIBsCE+93Eaj3TOHy0tXGe3Lb2qBkjhQfAs3RRmwqXGrdBV5guxoTafiWG7pr2IpOsYqKMz3SQ+FzWuxOEjbsoLONaOvPEmgs+IDgEq9fjg67Q1NpbnqhTF6r/PooQ/v2PWTzOaXmhDlJomVU3FVvkmbThkKeYbJDdZ5L5BT++NOxNdcj/wFvJ+j2MVYOKPW01ZAhE0GTmJc9M2WP/iZiapewVC+La/umlQX59wdI8dpejQNIDJgLiHkrgOGB+rgaaAYP6WRE1UdqI7qFaCHObMXeHSab9vQHB1OAyYNsocLEXLwck0yoWyqCm4MP2wh3diQd3LZ0TTxIMuBB4XmAO9YAsOEqiI8IesPfrVcqeX1SIdPVkf01q7SZoGqF0j1rfoUDe2EkFhdcjyYmMo/s1GZIyf5vOnowDU5Fq3GJVERaUFfaOzVI6QsIgEoW2jD4qJ7sLols6tcHwO1uZIq0mc68U3+Ww5D/C/SRiyGzSPRdFrF4WTcpwsZFZ/6SFvNqKNJPrhPc9C3dvWfcjG8mQvarlTdKhf8OUhIv/kPahZbCwMS1my15YdLdFURkAl/tY1ojuXLlL4kjXYW47sARp87Zw1Ton3SIWhnRJZKfTj1izDiTMiVEebBSmtyoij7BZeBLRPKdjzXkNthdhJH+GriF+tRug2ipvJZ1Grn+oY145RBHKTwhc8Gpd2+m6WCxI/7VO7T2fPtuSSfDwQN0D3pXxDCfyfZvsnp8c5i8spMZh8mnPOQoGBCje4xf/kvq7EpJz8nPRSgEIiYvjEkm2qk6JiCtw3YRN8arG8TvNuh5t2KsIXPwQT28pO9NyTIHcXaQkhfXlkCANhKqI9yanaZBwRucyEHW3DfjdRAQfF3whOdQ3IJeuW16I06fpGZu4Wmgkphjj0HtYTWMQM6N/rZmpDjKbWlWYedt7voI/df/AM6NJLyyRG4VK+wTJD9jWHI/I50v6c0yZqL2fYu9HHnC7U/A+DgMMnWg25OCbZuJNYvMAu314KdICl3cgxxB86yN1nrdLAKyVNwQO5tgY3mR/ED5I0083pp2J8Vfem8IV/afgr9Pqs4D5MJ/YWZkQz6Wn/54Vh0FOwx4py8WfU67E3nwlQBqCj8t0m3+BQI9dud7SOfGejGbkhwf7CnFjmL7t4EXUIgd+Hfh+C5OCbhGFvT3ILzJ77KqlI+ENpAKBD7MUX02d3HbGtcbJ/D9N9+vks/giXvSJNO0vOHsQsSqTTMSYfOv2rmN7NLA087L0y/5a6RRrLx8m17JNq728swW9zXloORwp0gEcPsxx6TJqRuUhEYWN7m35fbP46wKiCVtfhD1ICnwEBIngElBPgzfjQKB1HKPrG4z5vAi+ekeiFsQLGPa9HV3cav/8WUBBwjR8kytH0ETWIaNKZ382osqbAcV7W+fga3VL3d+m1dhvslcWn7x9HXMRA1XnX7kmendtfomDoZzBziqkFRUt5+nSzP+GZ4ANc1VEjgEwCNIeXMDNBw4qeCkyXHCyGN/H7eF2UF7R/P1McBdWb7AP8dqeRtcVWPs6xFdaa9Rhz5NFt6ZGMxV1JcGpj5RTZpvHMxmIr7VFh4UINSMsDl1xaiP/My9JbSVtEnDzgQOm0P5muiGl+ICMnnQMqqNO1xTAeKnl1WPigmrr8oOYvcsrDm/codxpupodEiMqbQryqxcvDB7ittoKgkMzp8JLLwtCCywvrH2SxhXR+dP8BWGXmw3TpfRuqPr0H2O69mnf5TbvKAHCRbgAnea+zcFuGWJinqmFef6OjtqWSKDN1rdC4LycrafkCGpR2pmKsS8CYcJiA89DQzxB+Zey1KC10CHzENdKX0bYOC3tuI68mQMuqmgxrwmAqhmt44H+jWBJrfNETkexTWLhSXzCgVeeGoZPLSTfM2dEXrXb6bclFY7aotH7zXoi4qvFxd5sXHm6qddtiWwonTDSuEYEKmTi2K1c4alcNjKbVJ/xTsj7iuPNVeuuWEUpt3CvR2wPNCfE+7i9wiMkluM/H+O9GBEUKZc75fRMJECGnPO4m03HQpZlk579Gs8OM2VnoI5nrvk5za0xHNWIz5eDNNuWMymmKWHtzq7oitbzGUeOq5MZ/dTsQDpsOgT3ev8hZsF7g/l6DxcyNuFemALLI4iMT7YNmHINLzNUd1fQ4jcmdRndYk1ajw6tWJXWREHcKugnbOg4Qj1+EI38tOGniAVCMRfusRMZRffBKfF9BHlYPDgvHwsgJ0axos2HkifibIit+QLjerp9NxvNhgApaQRR7gjTsqsvZHdxzR/ILhl6zPdrzgcBve6QASjKOgrSKa7JWGHnjrWfiUvTa2UlACx3gYcyqAPiC1zlx8DH6PGqqZ9Wp+NfoM0DLaORPkmeOIRyjSAZaV2/EFKBuALeDtxA/pjVPvuNKDV3W/Sp26SA+J3RmsVo0a2a00kp2eTc7nOREMacXzVU6EqTESbI995FIcc/XQ3h+ZHvVCFxn+qDL2FR2Y8tODZqL+gL0ulnWy/P2d1Zb9mMoDm5CAFeG0PjDP/6kDPZf6JiuhcQtb/G7Ph+PbnKqmKUUNU/VFefdxjFlJe7DS8yC1IE/S3dG1TFCpFhAJkDMJEHXXdbCnPVX9+esSVlLqvHOYO53DtW+fjKocP429LCaORwGGUMhD6x3oEXVlFs9Ljl6fTE53GgDxuD0y1VI5OWTdC4mQzw9Fi14xKKeQsEJ+R57bmxidtgAv4GPPPQhPExx+G53HJf4mbr9uiQJlBtSyolzTDmBwTlb4fQKcwCFTL5bOjOs8ITv0z/bc9H3GPvjnaolnbvOcqH7j0NBo+KTNYQQXbwr5t8XIiLuZppLKZuiO6JHKRXHiEKeeqnw+gomE/DlwlYFkZHms/empUh2fGIEpPsUnzN3Cb/T/c4EZCaMI42CbOdz1vLLizzgvAYksEXNwqtphPN2LlhTA3ebff3Gx98IBRTmx2B3DB928D9db8UHsJO9ua+dj6/OhKXraS+dIE7hUt2SnOh8u5upyGlXJXwn+BS8Sfk95vCUwAXFjmmyqMDgDIVMW9z5vFRBlSKi/5xE32CVBCLXkQsS+cA2qOKs2DIbCqpk3AgTx2iFoOBqbO7lPrxNG/pQRLK6iVS5B+jd7CsAe/KkWJTer2eC8WaC+MvHQtLoEp3C76hJdMFW9q++95KhFbdqY+Aoe3AAA) **Figure : Expected output for gst-ai-segmentation application** ## Pipeline flow The following table lists the plugins used in the image segmentation pipeline: | Plugin | Description | | --- | --- | | Camera source: [qtiqmmfsrc](https://docs.qualcomm.com/doc/80-80022-50/topic/qtiqmmfsrc.html) |

  • Captures the live stream from camera.


  • Uses tee to split the stream for inferencing.


| | File source: filesrc |

  • Captures the video stream using filesrc, followed by qtdemux, which demultiplexes the stream.


  • Uses tee to split the stream for inferencing.


| | RTSP source: rtspsrc |

  • Captures the RTSP stream using rtspsrc, followed by rtph264depay for video extraction.


  • Uses tee to split the stream for inferencing.


| | h264parse | Parses the H.264 video. | | [v4l2h264dec](https://docs.qualcomm.com/doc/80-80022-50/topic/v4l2h264dec.html) | Decodes the video. | | [qtimlvconverter](https://docs.qualcomm.com/doc/80-80022-50/topic/qtimlvconverter.html) |

  1. Receives the video stream on its sink pad.


  2. Performs the following preprocessing on the stream data. This preprocessing is done when the model expects floating-point values as input.


    1. Color conversion


    2. Scaling (up or down)


    3. Normalization




  3. Converts the preprocessed video stream to a tensor stream on its source pad.




The tensor stream is used for inferencing in the later stages of the pipeline. | | Inferencing plugins:
|

  1. After the inference runtime receives the tensor stream on its sink pad, it runs the inference.


  2. Produces a tensor stream with the inference results on its source pad.


| | [qtimlpostprocess](https://docs.qualcomm.com/doc/80-80022-50/topic/qtimlpostprocess.html) | Converts the inference tensors received on sink pad into video formats that the multimedia plugins use for further processing. | | [qtivcomposer](https://docs.qualcomm.com/doc/80-80022-50/topic/qtivcomposer.html) |

  1. Composes frames by combining content from its sink pads.


  2. Pushes the GStreamer buffers containing these composed frames to its source pad.


| | [waylandsink](https://docs.qualcomm.com/doc/80-80022-50/topic/waylandsink.html) |

  1. Forwards the video stream received on its sink pad to Weston.


  2. Weston renders the video stream on a local display.


| ## Config JSON field description The different parameters available to configure the JSON file and run the use case are as follows: Table : Field description–config_segmentation.json file | Field | Values/description | | --- | --- | | **ml-framework** | Enable and use one of the following models:

  • snpe: Qualcomm Neural Processing SDK


  • tflite: LiteRT


  • qnn: Qualcomm AI Engine direct


| | **runtime** | Enable and use one of the following runtimes:

  • cpu


  • gpu


  • dsp


| | **Input source** | Enable and use one of the following input sources:

  • camera: Primary (0) or secondary (1).


  • file-path: The directory path to the video file.


  • rtsp-ip-port: The address of the RTSP stream: rtsp://<ip>:<port>/<stream>.


| ## Related information - [Image segmentation and display with LiteRT](https://docs.qualcomm.com/doc/80-80022-50/topic/single-camera-stream-with-image-segmentation-and-display.html) - [Image segmentation and encode with LiteRT](https://docs.qualcomm.com/doc/80-80022-50/topic/single-camera-stream-with-image-segmentation-and-encode.html) - [Image segmentation and display with Neural Processing SDK](https://docs.qualcomm.com/doc/80-80022-50/topic/single-camera-stream-with-image-segmentation-and-display-with-deeplabv3-quantized.html) - [Image segmentation and encode with Neural Processing SDK](https://docs.qualcomm.com/doc/80-80022-50/topic/single-camera-stream-with-image-segmentation-and-encode-with-deeplabv3-quantized.html) Last Published: May 17, 2026 [Previous Topic Pose detection](https://docs.qualcomm.com/bundle/publicresource/80-80022-55/topics/gst-ai-pose-detection.md) [Next Topic Image segmentation using Python with container](https://docs.qualcomm.com/bundle/publicresource/80-80022-55/topics/image-segmentation-using-python.md) Source: [https://docs.qualcomm.com/doc/80-80022-55/topic/gst-ai-segmentation.html](https://docs.qualcomm.com/doc/80-80022-55/topic/gst-ai-segmentation.html)