yolov3_tiny_tf run_inference_stream problem - yolov3_tiny_tf run_inference_stream problem i have completed successfully Arria 10 SoC demo project resnet-50-tf on Arria 10 SoC devkit. (my tool version intel fpga ai suite 2025.1 and open vino 2024.6). i have used the precompile arria10 wic image. Arria 10 SoC devkit: https://www.altera.com/products/devkit/a1jui0000049utgmam/arria-10-sx-soc-development-kit SoC Demo project: https://www.intel.com/content/www/us/en/docs/programmable/848957/2025-1/soc-design-example-prerequisites.html Then, i have compiled yolo_v3_tiny_tf model with no folding and device fpga, cpu to obtain .bin file. When i run the ./run_inference_stream.sh, it get this error: root@arria10:~/app# ./run_inference_stream.sh Runtime version check is enabled. [ INFO ] Architecture used to compile the imported model: A10_Performance Using licensed IP Read hash from bitstream ROM... Read build version string from bitstream ROM... Read arch name string from bitstream ROM... Runtime arch check is enabled. Check started... Runtime arch check passed. Runtime build version check is enabled. Check started... Runtime build version check passed. Exception from src/inference/src/cpp/core.cpp:184: Exception from src/inference/src/dev/plugin.cpp:73: Exception from src/inference/src/dev/plugin.cpp:73: Exception from src/plugins/intel_cpu/src/utils/serialize.cpp:145: [CPU] Could not deserialize by device xml header. How can i solve this problem? Thank you. Note: root@arria10:~/app# ls build_os.txt libopenvino_auto_batch_plugin.so build_version.txt libopenvino_auto_plugin.so categories.txt libopenvino_c.so dla_benchmark libopenvino_c.so.2024.6.0 hetero_plugin libopenvino_c.so.2460 image_streaming_app libopenvino_ir_frontend.so libcoreDLAHeteroPlugin.so libopenvino_ir_frontend.so.2024.6.0 libcoreDlaRuntimePlugin.so libopenvino_ir_frontend.so.2460 libformat_reader.so libopenvino_jax_frontend.so libhps_platform_mmd.so libopenvino_jax_frontend.so.2024.6.0 libopencv_core.so.4.8.0 libopenvino_jax_frontend.so.2460 libopencv_core.so.408 libopenvino_pytorch_frontend.so libopencv_highgui.so.4.8.0 libopenvino_pytorch_frontend.so.2024.6.0 libopencv_highgui.so.408 libopenvino_pytorch_frontend.so.2460 libopencv_imgcodecs.so.4.8.0 libopenvino_template_extension.so libopencv_imgcodecs.so.408 libopenvino_tensorflow_lite_frontend.so libopencv_imgproc.so.4.8.0 libopenvino_tensorflow_lite_frontend.so.2024.6.0 libopencv_imgproc.so.408 libopenvino_tensorflow_lite_frontend.so.2460 libopencv_videoio.so.4.8.0 plugins.xml libopencv_videoio.so.408 results.txt libopenvino.so run_image_stream.sh libopenvino.so.2024.6.0 run_inference_stream.sh libopenvino.so.2460 streaming_inference_app libopenvino_arm_cpu_plugin.so Replies: Re: yolov3_tiny_tf run_inference_stream problem Glad to hear that the issue is resolved. Replies: Re: yolov3_tiny_tf run_inference_stream problem I have solved the error ([CPU] Could not deserialize by device xml header) by modifying the model xml file. Run the dla_compiler and then get the unsupported layers name. Delete the unsupported layers from xml file and compile again to obtain IR data. Error would disappear. Replies: Re: yolov3_tiny_tf run_inference_stream problem Hi, You may refer to https://www.intel.com/content/www/us/en/docs/programmable/768972/2025-1/estimating-the-performance-of-a-graph.html to check if the design can be run on the FPGA AI Suite architecture. Replies: Re: yolov3_tiny_tf run_inference_stream problem I could not understand what I exactly should change the run_image_stream and/or image_streaming_app (c++ codes) to run the hetero models with supported and unsupported layers? Is there any guide or something to clarify? I expect to run the model with supported layer and then it gives me outputs for supported layers, later execute the cpu codes for unsupported layer. Replies: Re: yolov3_tiny_tf run_inference_stream problem Hi, I am glad that you understand it. Please let me know if you have any other queries. Replies: Re: yolov3_tiny_tf run_inference_stream problem If the run_image_stream and/or image_streaming_app code are modified according to unsupported layers, then the yolo-v3-tiny model will run successfully, what you are trying to tell me as i got it. Thank you. Replies: Re: yolov3_tiny_tf run_inference_stream problem Hi, Have you performed some emulation to confirm if the model you are using is able to be run in FPGA? The reason is that the example provided is to have the model fully run in FPGA. But based on the log file provided, some of the layer is not able to performed in FPGA and it need to revert to CPU but the Application code does not support it. It is recommended you try to compile graph and check the output if it is fully supported or not. https://www.intel.com/content/www/us/en/docs/programmable/863373/2025-3/compiling-a-graph.html. Replies: Re: yolov3_tiny_tf run_inference_stream problem Actually, i did not any change on the run_image_stream.sh or stream.sh. I used the below wic file from example project. $COREDLA_ROOT/demo/ed4/a10_soc_s2m/sd-card/coredla-image-arria10.wic https://www.intel.com/content/www/us/en/docs/programmable/848957/2025-1/writing-the-sd-card-image-wic-to-an-sd-card.html Replies: Re: yolov3_tiny_tf run_inference_stream problem Hi, Have you modify the run_image_stream.sh? If yes, can you share with me what is the changes performed? What is the FPGA design or bitstream used? Thanks