Training and Prediction Scripts for CNTK Faster-RCNN

These script removes a lot of the manual edits needed for the config files, downloading of models, and setup of annotations necessary to run the CNTK detection example.

You can use the CNTK dockerfile located here and then place train.py and predict.py in /cntk/Examples/Images/Detection.

Before Training

Set up your custom image directory in the format required by CNTK. The directory will be structured as:

.
├── negative
│ ├── a0vqvtsowhoubmczrq4q.jpg
│ ├── avhrylgho1dg1ns6q6wb.jpg
│ └── ictav2a3ahahv2pcusck.jpg
├── positive
│ ├── aljrnxc0ttj07dc2riel.bboxes.labels.tsv
│ ├── aljrnxc0ttj07dc2riel.bboxes.tsv
│ ├── aljrnxc0ttj07dc2riel.jpg
│ ├── icde4ql7u7clfv3lmani.bboxes.labels.tsv
│ ├── icde4ql7u7clfv3lmani.bboxes.tsv
│ └── icde4ql7u7clfv3lmani.jpg
└── testImages
 ├── bz7mfvk1etwl0rzofewu.bboxes.labels.tsv
 ├── bz7mfvk1etwl0rzofewu.bboxes.tsv
 └── bz7mfvk1etwl0rzofewu.jpg

Training and Prediction Parameters

tag	value expected
gpu	To use gpu in either training or prediction, specify 1. Otherwise, cpu will be used.
tagged-images	Provide a path to the directory containing your custom images prepared for CNTK object detection. The directory should contain information formatted as described here. I recommend using the VoTT tool to create the formatted directory.
num-train	The number of training images used to train the model.
num-epochs	The number of epochs used to train the model. One epoch is one complete training cycle on the training set.
num-test	The number images to test.
model-path	The path to your trained model. To get a trained model, run train.py. The training script will output the directory where your trained model is stored. Also, you can look at the model path below, since that is the expected path where your model will reside when you run the training.
conf-threshold	The confidence threshold used to determine when bounding boxes around detected objects are drawn. A confidence threshold of 0 will draw all bounding boxes determined by CNTK. A threshold of 1 will only draw a bounding box around the exact location you had originally drawn a bounding box, i.e. you trained and tested on the same image. Provide a float falling between 0 and 1. The default confidence theshold is 0.

Training

python train.py
  [--gpu 1] 
  --tagged-images /CustomImages
  --num-train 200 
  [--num-epochs 3]

Training Output

After you run training, /cntk/Examples/Image/Detection/FasterRCNN/Output/ will contain one new item:

• faster_rcnn_eval_AlexNet_e2e.model - trained model used as input for predictions

Predictions

python predict.py
  [--gpu 1] 
  --tagged-images /CustomImages 
  --num-test 5
  --model-path /cntk/Examples/Image/Detection/FasterRCNN/Output/faster_rcnn_eval_AlexNet_e2e.model
  [--conf-threshold 0.82]

Prediction Output

After you run your predictions, /cntk/Examples/Image/Detection/FasterRCNN/Output/ will contain two new items:

• CustomImages directory - contains custom images with bounding boxes drawn on detected objects
• custom_images_output.json - json output of bounding boxes, confidence levels, and class names for each image

custom_images_output.json

{ "images": 
  {
    "/Reverb/labelled-guitars/testImages/adfvzfswiuv0a1erna5k.jpg": {
      "class": "body",
      "bounding_boxes": [
        {"confidence_level": "0.536132", "bounding_box": {"x1": 317, "x2": 799, "y1": 65, "y2": 493}},
        {"confidence_level": "0.632784", "bounding_box": {"x1": 0, "x2": 389, "y1": 167, "y2": 507}},
        {"confidence_level": "0.767789", "bounding_box": {"x1": 0, "x2": 799, "y1": 102, "y2": 595}},
        {"confidence_level": "0.588904", "bounding_box": {"x1": 527, "x2": 780, "y1": 96, "y2": 579}},
        {"confidence_level": "0.743675", "bounding_box": {"x1": 0, "x2": 512, "y1": 196, "y2": 718}}
      ]
    }, 
    "/Reverb/labelled-guitars/testImages/aayjfcuulg99o3zpctux.jpg": {
      "class": "body", 
      "bounding_boxes": [
        {"confidence_level": "0.872948", "bounding_box": {"x1": 79, "x2": 582, "y1": 136, "y2": 764}},
        {"confidence_level": "0.629768", "bounding_box": {"x1": 158, "x2": 594, "y1": 180, "y2": 552}}
      ]
    },
    "/Reverb/labelled-guitars/testImages/caaqxk85v3izwweqvbsi.jpg": {
      "class": "__background__",
      "bounding_boxes": []
    }
  }
}