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August 1, 2019 12:55
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Code for training custom object detection model with ImageAI
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from imageai.Detection.Custom import DetectionModelTrainer | |
trainer = DetectionModelTrainer() | |
trainer.setModelTypeAsYOLOv3() | |
trainer.setDataDirectory(data_directory="hololens") | |
trainer.setTrainConfig(object_names_array=["hololens"], batch_size=4, num_experiments=100, train_from_pretrained_model="pretrained-yolov3.h5") | |
trainer.trainModel() |
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I am having an issue where it is not seeing, or evaluating my validation samples.
As per the walk through provided at https://medium.com/deepquestai/train-object-detection-ai-with-6-lines-of-code-6d087063f6ff
I have split my images and annotations roughly 75% 25% between train and validation folders.
there are 69 files in each of the respective images and annotations folder within the validation folder.
when I run the 6lines I am returned
Generating anchor boxes for training images and annotation...
Average IOU for 9 anchors: 0.91
Anchor Boxes generated.
Detection configuration saved in Samples_forTraining\json\detection_config.json
Evaluating over 0 samples taken from Samples_forTraining\validation
Training over 203 samples given at Samples_forTraining\train
Training on: ['SnowMeter']
Training with Batch Size: 4
Number of Training Samples: 203
Number of Validation Samples: 0
Number of Experiments: 100
Training with transfer learning from pretrained Model