Hi !
This is a sequel part after yesterday post on the new Model Builder Object Detection scenario. I’ve found this error, and it took me some time to figure out the reason.
As usual, an error on the Model Builder, with very few details and the suggestion to check more details on the Azure ML Portal.
On the Azure ML Portal, we can see that 3 experiments failed. Now is time to fig into the logs files and try to figure out what happened.
On the main experiment, after reading the logs, I found out that there is a [File missing for image]. And other file related issues.
And, after some research (test, fail and test again)
I realized that some of my original file names have a space on the file name.
In example [apple 04.png].
When we create the labeling project using VoTT, the exported project makes some changes into the file names and [apple 04.png] becomes [apple%2004.png]. Here is a part of the exported project:
{
"name": "mlnet bad file name",
"securityToken": "mlnet bad file name Token",
"videoSettings": {
"frameExtractionRate": 15
},
"tags": [
{
"name": "apple",
"color": "#5db300"
}
],
"id": "aajYgiNHg",
"activeLearningSettings": {
"autoDetect": false,
"predictTag": true,
"modelPathType": "coco"
},
"version": "2.2.0",
"lastVisitedAssetId": "3d30adce06faf9bf8c6540ec6435ef61",
"assets": {
"3d30adce06faf9bf8c6540ec6435ef61": {
"asset": {
"format": "png",
"id": "3d30adce06faf9bf8c6540ec6435ef61",
"name": "apple%2004.png",
"path": "file:C:/ML/FreshFood/mlnet%20bad%20file%20names/apple%2004.png",
"size": {
"width": 584,
"height": 510
},
"state": 2,
"type": 1
},
"regions": [
{
"id": "4BDOAk0Xq",
"type": "RECTANGLE",
"tags": [
"apple"
],
"boundingBox": {
"height": 505.0856531049251,
"width": 579.0878504672897,
"left": 1.782359813084112,
"top": 1.6381156316916488
},
The solution, was to use a tool and remove all the spaces and non-standard characters from my image data set. I also did all the labeling process again, and when I launched again my Object Recognition scenario from Model Builder, everything worked fine!
Resources
- VoTT
- VoTT Releases
- ML.NET Model Builder GPU vs CPU test: 4 times faster !
- MLNet – AutoML for ranking scenarios
- ML.NET Model Builder GPU Support (Preview)
- ML.NET Model Builder training using GPU, CPU and … Azure !
- ML.NET Model Builder for Object Detection using Azure Compute
- How to install GPU support in Model Builder
- August ML.NET API and Tooling Updates
- State Farm Distracted Driver Detection
- How to Train TensorFlow Models Using GPUs
El Bruno 