Changing default detection model to run on Axis camera (Urgent) about acap-computer-vision-sdk-examples

[garaujo23]

Try running docker system prune -f --volumes on the camera to remove the model volume, should then have your new model. From your host PC you can also run docker -H tcp://$AXIS_TARGET_IP:$DOCKER_PORT system prune -af

[BenJam29]

Thanks a lot @garaujo23 for your comment. When I want to rebuild the object detector I use the following bash script. The command you mentioned is executed and old volumes are deteted. The code is attached below.

#!/bin/bash

: ' Description:

object-detector-python
├── app
├── |- detector.py
├── |- dog416.png
├── docker-compose.yml
├── static-image.yml
├── Dockerfile
├── Dockerfile.model

detector.py - The inference client main program
dog416.png - Static image used with static-image.yml
docker-compose.yml - Docker compose file for streaming camera video example using larod inference service
static-image.yml - Docker compose file for static image debug example using larod inference service
Dockerfile - Build Docker image with inference client for camera
Dockerfile.model - Build Docker image with inference model
'

# cd to hello world app directory
SCRIPT_DIR="$( cd -- "$( dirname -- "${BASH_SOURCE[0]:-$0}"; )" &> /dev/null && pwd 2> /dev/null; )"
cd $SCRIPT_DIR/../apps/object-detector-python

# For arm64 (Q1656-LE the architecture is arm64)
export ARCH=aarch64
# Valid options for chip on aarch64 are 'artpec8' (hardware accelerator) or 'cpu'
export CHIP=artpec8

# Camera Setup
export AXIS_TARGET_IP=206.174.180.54
export DOCKER_PORT=7581

# Define APP name
export APP_NAME=acap4-object-detector-python
export MODEL_NAME=acap-dl-models

# Clean docker memory
printf "\n#################### Cleaning docker memory ... ####################\n"
sudo docker -H tcp://$AXIS_TARGET_IP:$DOCKER_PORT system prune -af

# Install qemu to allow build flask for a different architecture
printf "\n#################### Installing qemu to allow build flask ... ####################\n"
sudo docker run -it --rm --privileged multiarch/qemu-user-static --credential yes --persistent yes

# Build and upload inference client for camera
printf "\n#################### Building and uploading inference client for camera ... ####################\n"
sudo docker build . -t $APP_NAME --build-arg ARCH
sudo docker save $APP_NAME | docker -H tcp://$AXIS_TARGET_IP:$DOCKER_PORT load

# Build and upload inference models
printf "\n#################### Building and uploading inference models for camera ... ####################\n"
sudo docker build . -f Dockerfile.model -t $MODEL_NAME --build-arg ARCH
sudo docker save $MODEL_NAME | docker -H tcp://$AXIS_TARGET_IP:$DOCKER_PORT load

The output for rebuilding is:

#################### Cleaning docker memory ... ####################
[sudo] password for behnam:             
Deleted Containers:
e95cb52a1d0275bcce18b7a16e0553433cacd1ec1e64ecc7f0fe63846a59e7fd
3cc1d47d05013ca4ffa0f5aee2d417ead829180016f1814248cee49c68be2f65
bc2f39af66ba4706d67d13717ac2de4186813e9c65b11265875ad810826a3230

Deleted Networks:
object-detector-python_default

Deleted Images:
untagged: acap-dl-models:latest
deleted: sha256:3e638375e811aca74d39efef1b2266b0d58b40d2c478822d70c39fd6694f88f7
deleted: sha256:917deb131fe665a035e67b7af025b0d53cd29d84e8acd08bcd8f7c80caa8079f
deleted: sha256:79fb712db44287bf7b7657449a13bf0f1162dcffef0cd254c88ff1240fd05878
deleted: sha256:ecc28deef19c7fc5036e69cc6d7a0dec47fd7a4e0bfdb94b0f1b858884ebd2dc
deleted: sha256:c695fdbbe117cff430b6567dbb4519464ec9b29cd2861a20ca489be7a2775ef0
deleted: sha256:dd565ff850e7003356e2b252758f9bdc1ff2803f61e995e24c7844f6297f8fc3
untagged: axisecp/acap-runtime:0.6-aarch64
untagged: axisecp/acap-runtime@sha256:f9d4ad68d33ac2e5bca477bae1af9b9d50dbd354dafa53d9424c296423c5c35f
deleted: sha256:7af88c670dc7284e17e6b9fa99c84ec4be13d31f78cc6ad3f33343e8f8eb07c2
deleted: sha256:b77f4975d4d018b7f07443312493178a22cfff851da75e80e53764a9f7f81f34
deleted: sha256:e8e3a4ee8de1ec9e6a48eaf4d5a1a5e833a8073dddba573cce5ed539ecf9d05f
deleted: sha256:4e3a47641eef414a8e4c324c0908d036bde9e4703d7ab12c8c7a1300efb70c78
deleted: sha256:a12b9bea33ecfc12c88e5bf55eb20d6e8522ea2749a163b31fc9f69cd787b828
deleted: sha256:432b3de25d92b22b3c362467bfbbb8bb6611163ad858e8ac662955608e56ee5e
deleted: sha256:f94736c0f7a0f1defeb9f6398c2322ba861fab6e4cd7ab036f8751e70decd66a
deleted: sha256:b753a71ec0efa96f79239330227ba465a297f7f74798d97ac2aa3ffce91e4700
deleted: sha256:b88c694e50d0f2276d37418dd9f81f574cbd3de73d68a84e3d509cc0f72ee697
deleted: sha256:c55ac170e0177d374f6be4136823a070495e8fe80046a5867e1a1477ab9848d4
deleted: sha256:d3636593414b57373747f7df90de0459054dd2b3a1ac35a3b0b647dc702702d5
deleted: sha256:0819900094fcbf63ee4a843c7185f124e8748c2933bcb8fa3f43c6f09a0d8205
deleted: sha256:7dbfce9d1310108bd44fc0b0a84335f26f133ff91ea672b11e5a70dfd1228a51
deleted: sha256:055538203431597fd1b320db1682dd1478395ce42ffa883c30ba7bd19db58497
deleted: sha256:eab5e90eef28773e05560aac1900b203c6f8356bcd4d8dc78f00219a09b4264f
deleted: sha256:81b46cc6b3d699b968a933f403c1cae3fc6daaeddc1abf5ee45617c72ffcaeba
deleted: sha256:038d0573c9f62181b3ef070fccd5b75512b246c8762230617f3a52375df4acfd
deleted: sha256:8941214bcd17e54ff3f98ab30d538a7f61cc0b8165b4ca39aa02e98096d2abbd
deleted: sha256:f615dace8722bb91d54f30ce7bdbbd70ce39ff760a73eadbf2bc88897a1bc83b
deleted: sha256:dc8ce6c30712bfd583e0e8ef27c36886240ac6921c6ead81d28c14f7f3816cd3
deleted: sha256:a8fbf9f278fc7b31173a095a31c4a43a5fca39864c7b65588a81546b29075183
deleted: sha256:992bf51e74e0992dbf9d4a5def169463d13b551f97453fab5c7ba3717e6de42b
deleted: sha256:4fc005e132e201536501a631d6ed22d79db5093e82ec2887f4fefca64e05050d
deleted: sha256:34fed83d22fa86c27902bae18b734ba4bc17158c2ff3ffa831a325d8757ad8b4
deleted: sha256:eb41b83fbfe7d00e5872257db46a4e9741e048b9729273c985177b48471b029f
deleted: sha256:350f36b271dee3d47478fbcd72b98fed5bbcc369632f2d115c3cb62d784edaec
untagged: acap4-object-detector-python:latest
deleted: sha256:d5e0a31dd793a9a195d23da1de7990a101cc17f36e1e2a6d4032e2458c7a65bf
deleted: sha256:7fa6e907c2ad7f67b0086f21566197fd4daad50c80636fe66be254a48f311ea2
deleted: sha256:41abc841d6d99446debbe06f6ef0c5d14ba2108d132cd196cd6a75f6d3f5a6da
deleted: sha256:c2b78bfb4ea1ded88e137e74e4d3313dac708b634e617b1b16847ca61c3204e9
deleted: sha256:929bac34d18325734a02bdc5c1ef5ae8b49a0a4e25bd0af3a6081196378fca5d
deleted: sha256:f0885049cdc187d4c3ee4764c1e1ecd6db15da447e0310eaf754dd5e0f6c39c4
deleted: sha256:040325e4a34ef5868ded9cbc27999a42961fedf01278ffb28487bc50a1c3e7ae
deleted: sha256:0557987b9395d985733b80569a0465aceeaaf2ece0fcbaf9a9ca42aaef647bd6
deleted: sha256:e265835b28ac16782ef429b44427c7a72cdefc642794515d78a390a72a2eab42

Total reclaimed space: 730.8MB

#################### Installing qemu to allow build flask ... ####################
Setting /usr/bin/qemu-alpha-static as binfmt interpreter for alpha
sh: write error: File exists
Setting /usr/bin/qemu-arm-static as binfmt interpreter for arm
sh: write error: File exists
Setting /usr/bin/qemu-armeb-static as binfmt interpreter for armeb
sh: write error: File exists
Setting /usr/bin/qemu-sparc-static as binfmt interpreter for sparc
sh: write error: File exists
Setting /usr/bin/qemu-sparc32plus-static as binfmt interpreter for sparc32plus
sh: write error: File exists
Setting /usr/bin/qemu-sparc64-static as binfmt interpreter for sparc64
sh: write error: File exists
Setting /usr/bin/qemu-ppc-static as binfmt interpreter for ppc
sh: write error: File exists
Setting /usr/bin/qemu-ppc64-static as binfmt interpreter for ppc64
sh: write error: File exists
Setting /usr/bin/qemu-ppc64le-static as binfmt interpreter for ppc64le
sh: write error: File exists
Setting /usr/bin/qemu-m68k-static as binfmt interpreter for m68k
sh: write error: File exists
Setting /usr/bin/qemu-mips-static as binfmt interpreter for mips
sh: write error: File exists
Setting /usr/bin/qemu-mipsel-static as binfmt interpreter for mipsel
sh: write error: File exists
Setting /usr/bin/qemu-mipsn32-static as binfmt interpreter for mipsn32
sh: write error: File exists
Setting /usr/bin/qemu-mipsn32el-static as binfmt interpreter for mipsn32el
sh: write error: File exists
Setting /usr/bin/qemu-mips64-static as binfmt interpreter for mips64
sh: write error: File exists
Setting /usr/bin/qemu-mips64el-static as binfmt interpreter for mips64el
sh: write error: File exists
Setting /usr/bin/qemu-sh4-static as binfmt interpreter for sh4
sh: write error: File exists
Setting /usr/bin/qemu-sh4eb-static as binfmt interpreter for sh4eb
sh: write error: File exists
Setting /usr/bin/qemu-s390x-static as binfmt interpreter for s390x
sh: write error: File exists
Setting /usr/bin/qemu-aarch64-static as binfmt interpreter for aarch64
sh: write error: File exists
Setting /usr/bin/qemu-aarch64_be-static as binfmt interpreter for aarch64_be
sh: write error: File exists
Setting /usr/bin/qemu-hppa-static as binfmt interpreter for hppa
sh: write error: File exists
Setting /usr/bin/qemu-riscv32-static as binfmt interpreter for riscv32
sh: write error: File exists
Setting /usr/bin/qemu-riscv64-static as binfmt interpreter for riscv64
sh: write error: File exists
Setting /usr/bin/qemu-xtensa-static as binfmt interpreter for xtensa
sh: write error: File exists
Setting /usr/bin/qemu-xtensaeb-static as binfmt interpreter for xtensaeb
sh: write error: File exists
Setting /usr/bin/qemu-microblaze-static as binfmt interpreter for microblaze
sh: write error: File exists
Setting /usr/bin/qemu-microblazeel-static as binfmt interpreter for microblazeel
sh: write error: File exists
Setting /usr/bin/qemu-or1k-static as binfmt interpreter for or1k
sh: write error: File exists
Setting /usr/bin/qemu-hexagon-static as binfmt interpreter for hexagon
sh: write error: File exists

#################### Building and uploading inference client for camera ... ####################
Sending build context to Docker daemon  439.3kB
Step 1/14 : ARG ARCH=aarch64
Step 2/14 : ARG SDK_VERSION=1.2
Step 3/14 : ARG REPO=axisecp
Step 4/14 : FROM arm64v8/ubuntu:20.04 as runtime-image-aarch64
 ---> db1bc6aa58da
Step 5/14 : FROM $REPO/acap-computer-vision-sdk:$SDK_VERSION-$ARCH AS cv-sdk
 ---> 0eaa6bb57def
Step 6/14 : FROM runtime-image-${ARCH}
 ---> db1bc6aa58da
Step 7/14 : COPY --from=cv-sdk /axis/python /
 ---> Using cache
 ---> 979e8195a241
Step 8/14 : COPY --from=cv-sdk /axis/python-numpy /
 ---> Using cache
 ---> a7ff49c5a010
Step 9/14 : COPY --from=cv-sdk /axis/python-tfserving /
 ---> Using cache
 ---> dbb56f713381
Step 10/14 : COPY --from=cv-sdk /axis/opencv /
 ---> Using cache
 ---> f0447d4cacf4
Step 11/14 : COPY --from=cv-sdk /axis/openblas /
 ---> Using cache
 ---> b57f43d55de9
Step 12/14 : WORKDIR /app
 ---> Using cache
 ---> 9abcf84e5341
Step 13/14 : COPY app/* /app/
 ---> Using cache
 ---> a686434caf70
Step 14/14 : CMD ["python3", "stage-1.py"]
 ---> Using cache
 ---> d5e0a31dd793
Successfully built d5e0a31dd793
Successfully tagged acap4-object-detector-python:latest

[Corallo]

Hi @BenJam29
The answer of @garaujo23 is correct, you need to make sure that the old volumes in your camera are removed.
First of all, make sure to run the command
docker-compose --tlsverify --host tcp://$DEVICE_IP:$DOCKER_PORT --env-file ./config/env.$ARCH.$CHIP down --volumes
when you terminate your execution, to leave the camera in a "clean state"
Try to run it now, and see if it already solves your issue,
Otherwise run
docker -H tcp://$DEVICE_IP:$DOCKER_PORT volumes ls to check if there are volumes left
and
docker volume prune -f to do a forced cleaning

[BenJam29]

Hi @Corallo,
Thanks a lot for your message. It was very helpful. In termination, the "--volumes" was missed in my script and now it removes all old volumes left on device (image attached below).

When rerun the program, the model name is correctly identified (image below), it failed to load the model. "ERROR in Inference: Failed to load model efficientdet_lite0_320_ptq_edgetpu.tflite (Could not load model: Could not set VX delegate)."

I use EfficientDet-Lite0 model from here, by copy pasting model url in Dockerfile.model.

Dockerfile.model content:

ARG ARCH=aarch64

FROM arm64v8/alpine as model-image-aarch64

FROM model-image-${ARCH}

# Get EfficientDet 0 Model
ADD https://raw.githubusercontent.com/google-coral/test_data/master/efficientdet_lite0_320_ptq_edgetpu.tflite models/
ADD https://raw.githubusercontent.com/google-coral/test_data/master/efficientdet_lite0_320_ptq.tflite models/
ADD https://github.com/google-coral/edgetpu/raw/master/test_data/coco_labels.txt models/
ADD https://github.com/google-coral/edgetpu/raw/master/test_data/COPYRIGHT models/

CMD /bin/ls /models

Any idea, why it failed to load new model?

[BenJam29]

Just tried to look deeper into the issue. I persistently receive the "<_InactiveRpcError of RPC that terminated with:status = StatusCode.DEADLINE_EXCEEDED" by using various models. Image attached below.

I took a look at gRPC to have a better understanding of the problem but I couldn't resolve the issue yet.

Any help would be appreciated.
Best,

[Corallo]

HI @BenJam29

I am going to move this issue into the discussion tab, as this is not an issue nor an enchantment.