DOODS Container unable to start with edgeTPU included #64
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It's staying you don't have SSE4.1... What processor are you running this on? |
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This is on an LXC on Proxmox on a Dell PowerEdge with dual Intel Xeon E5-2670 CPUs.
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On Nov 7, 2022, 8:59 AM, Zach wrote:
It's staying you don't have SSE4.1... What processor are you running this on?
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Do you have a GPU attached to this? I would just use the |
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Actually the |
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And the E5-2670 definitely supports SSE 4.1 so I'm not sure why it would print that message unless it's running in a VM or something. Not sure how Proxmox does LXC. |
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Ok,
I'll fiddle with my Proxmox/LXC config a bit.
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On Monday, November 7th, 2022 at 9:20 AM, Zach ***@***.***> wrote:
And the E5-2670 definitely supports SSE 4.1 so I'm not sure why it would print that message unless it's running in a VM or something. Not sure how Proxmox does LXC.
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Figured it out. I actually had ended up going with a VM in Proxmox because it was easier to passthrough the USB Coral device. Changing the CPU type to "host" seems to have resolved that error: Now I have the web interface running and working, but the edgeTPUI detector is not configured. I added this entry to the bottom of the config.yaml and placed this in the same folder with the docker-compose.yaml and the "models" folder where I downloaded the tflite and labels files (the first two were there and are detected and available in the Web Interface): detectors: |
Using the docker run command in the instructions, I was able to run the container and use the web interface.
I then updated my configs for the Coral USB device and now I am getting this error:
4f4fb700ef54: Pull complete
c099e822da9e: Pull complete
Digest: sha256:e8e39ba734d0055e56c058d0b5e3953d691149baea7bd767a8fd003c95f34ebd
Status: Downloaded newer image for snowzach/doods2:amd64-gpu
Creating doods2_doods_1 ... done
Attaching to doods2_doods_1
doods_1 | The TensorFlow library was compiled to use SSE4.1 instructions, but these aren't available on your machine.
doods2_doods_1 exited with code 139
Here is my config.yaml (with the relevant entry for the edgeTPU at the bottom):
server:
host: 0.0.0.0
port: 8080
metrics: true
logging:
level: info
doods:
log: detections
boxes:
enabled: True
boxColor: [0, 255, 0]
boxThickness: 1
fontScale: 1.2
fontColor: [0, 255, 0]
fontThickness: 1
regions:
enabled: True
boxColor: [255, 0, 255]
boxThickness: 1
fontScale: 1.2
fontColor: [255, 0, 255]
fontThickness: 1
globals:
enabled: True
fontScale: 1.2
fontColor: [255, 255, 0]
fontThickness: 1
detectors:
- name: default
type: tflite
modelFile: models/coco_ssd_mobilenet_v1_1.0_quant.tflite
labelFile: models/coco_labels0.txt
hwAccel: false
numThreads: 4
- name: tensorflow
type: tensorflow
modelFile: models/faster_rcnn_inception_v2_coco_2018_01_28.pb
labelFile: models/coco_labels1.txt
hwAccel: false
- name: edgeTPU
type: tflite
modelFile: models/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite
labelFile: models/coco_labels.txt
hwAccel: true
numThreads: 4
And here is my docker-compose.yaml with the edgeTPU USB bus device passed to the container:
version: '3.2'
services:
doods:
image: snowzach/doods2:amd64-gpu
ports:
- "8080:8080"
devices:
- /dev/bus/usb/007/002
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