Classify a handwritten number
This endpoint classifies any image of a handwritten number that conforms to the image format. A neural network trained on the MNIST database of handwritten digits performs the classification.
|
The first invocation of Classify a handwritten zero or Classify a handwritten number trains the image recognition model, which takes approximately 10 - 20 seconds. The model is then cached for efficient subsequent invocations. Observe the training delay in the logs: Training: 100% |████████████████████████████████████████| Epoch 1 finished. Training: 100% |████████████████████████████████████████| Epoch 2 finished. |
Handwritten-zero request
Send the following request to explicitly process the same image processed by the Classify a handwritten zero
endpoint
:
{
"fileName": "0.png"
}Response
|
Data is truncated for readability. |
Notice that the image is recognised as 0, with a high probability of correctness:
{
"handwrittenNumber": "0",
"probabilities": [
{
"handwrittenNumber": "0",
"probability": 0.9999525547
},
{
"handwrittenNumber": "2",
"probability": 0.0000418071
},
{
"handwrittenNumber": "6",
"probability": 0.0000029869
}
]
}Ambiguous request
Send the following request to process an ambiguous image of a three that looks like an eight
:
{
"fileName": "3-that-looks-like-8.png"
}Response
|
Data is truncated for readability. |
Notice that the image is recognised as 3, with a lower probability of correctness than the less ambiguous
handwritten zero. Also notice that the second most probable match is 8:
{
"handwrittenNumber": "3",
"probabilities": [
{
"handwrittenNumber": "3",
"probability": 0.6336861849
},
{
"handwrittenNumber": "8",
"probability": 0.2507479191
},
{
"handwrittenNumber": "2",
"probability": 0.0491732359
}
]
}Custom request
Create a new image to experiment with the image recognition capabilities.
Image format
The image format is based on the MNIST database format. Images must have the following properties:
-
Resemble a number from zero to nine
-
Written in white with a black background
-
Sized 28x28 pixels
-
PNG format
Place the image in the
images source folder:
src/main/resources/images.
|
Stop, recompile and restart the application for the new image to be registered. As per the Install and run quickstart, this involves one of the following:
|
Verify registration via the List example input images endpoint.
Request body
Send a request structured as per the handwritten-zero request, substituting fileName with the name
of the created image.
Response
Expect a response structured as per the handwritten-zero response. Notice that the legibility of the handwritten number corresponds to the probability of correctness.