Deep Learning as a Cloud API Service.

Wu Han

Last update: Jan 6, 2023

Related tags

Deep Learning keras imagenet vgg16 inceptionv3 cifar10 resnet50

Overview

Deep API

Deep Learning as Cloud APIs.

This project provides pre-trained deep learning models as a cloud API service. A web interface is available as well.

Quick Start
API Client
- Using curl
- Using Python
Concurrent clients
Full APIs

Quick Start

Python 3:

$ pip3 install -r requirements.txt
$ python main.py

Anaconda:

$ conda env create -f environment.yml
$ conda activate cloudapi
$ python main.py

Using Docker:

docker run -p 8080:8080 wuhanstudio/deep-api

Navigate to https://localhost:8080

API Client

It's possible to get predictions by sending a POST request to http://127.0.0.1:8080/vgg16_cifar10.

Using curl:

```
export IMAGE_FILE=test/cat.jpg
(echo -n '{"file": "'; base64 $IMAGE_FILE; echo '"}') | \
curl -H "Content-Type: application/json" \
     -d @- http://127.0.0.1:8080/vgg16_cifar10
```

Using Python:

def classification(url, file):
    # Load the input image and construct the payload for the request
    image = Image.open(file)
    buff = BytesIO()
    image.save(buff, format="JPEG")

    data = {'file': base64.b64encode(buff.getvalue()).decode("utf-8")}
    return requests.post(url, json=data).json()

res = classification('http://127.0.0.1:8080/vgg', 'cat.jpg')

This python script is available in the test folder. You should see prediction results by running python3 minimal.py:

cat            0.99804
deer           0.00156
truck          0.00012
airplane       0.00010
dog            0.00009
bird           0.00005
ship           0.00003
frog           0.00001
horse          0.00001
automobile     0.00001

Concurrent clients

Sending 5 concurrent requests to the api server:

$ python3 multi-client.py --num_workers 5 cat.jpg

You should see the result:

----- start -----
Sending requests
Sending requests
Sending requests
Sending requests
Sending requests
------ end ------
Concurrent Requests: 5
Total Runtime: 2.441638708114624

Full APIs

Post URLs:

Model	Dataset	Post URL
VGG-16	Cifar10	http://127.0.0.1:8080/vgg16_cifar10
VGG-16	ImageNet	http://127.0.0.1:8080/vgg16
Resnet-50	ImageNet	http://127.0.0.1:8080/resnet50
Inception v3	ImageNet	http://127.0.0.1:8080/inceptionv3

Post Data (JSON):

{
  "file": ""
}

Query Parameters:

Name	Type	Default	Value
top	integer	10	One of [1, 3, 5, 10], top=5 returns top 5 predictions.
no-prob	integer	0	no-prob=1 returns labels without probabilities. no-prob=0 returns labels and probabilities.

Example post urls (returns top 10 predictions with probabilities):

http://127.0.0.1:8080/vgg16?top=10&no-prob=0

Returns (JSON):

Key	Value
success	True / False
Predictions	Array of prediction results, each element contains {"labels": "cat", "probability": 0.99}
error	The error message if any

Example returned json:

{
  "success": true,
  "predictions": [
    {
      "label": "cat",
      "probability": 0.9996376037597656
    },
    {
      "label": "dog",
      "probability": 0.0002855948405340314
    },
    {
      "label": "deer",
      "probability": 0.000021985460989526473
    },
    {
      "label": "bird",
      "probability": 0.000021391952031990513
    },
    {
      "label": "horse",
      "probability": 0.000013297495570441242
    },
    {
      "label": "airplane",
      "probability": 0.000006046993803465739
    },
    {
      "label": "ship",
      "probability": 0.0000044226785576029215
    },
    {
      "label": "frog",
      "probability": 0.0000036349929359857924
    },
    {
      "label": "truck",
      "probability": 0.0000035354278224986047
    },
    {
      "label": "automobile",
      "probability": 0.000002384880417594104
    }
  ],
}

References

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Releases(v0.1.0)

v0.1.0(Oct 26, 2021)
Deep Learning as a Cloud API Service that supports:

Pretrained VGG16 model on Cifar10 dataset

Pretrained VGG16 model on ImageNet dataset

Pretrained Resnet50 model on ImageNet dataset

Pretrained Inceptionv3 model on ImageNet dataset

Automatic python client code generation

Automatic curl client code generation

A web interface for the api service

A minimal version is deployed here:

http://api.wuhanstudio.uk/
Source code(tar.gz)
Source code(zip)