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Webpage docs

This is a basic web app to implement image recognition for predicting with local files and urls.

Preliminaries

You have to do some preliminary steps to select the model you want to predict with:

  • copy your desired .models/[timestamp] to .models/api. If there is no .models/api folder, the default is to use the last available timestamp.
  • in the .models/api/ckpts leave only the desired checkpoint to use for prediction. If there are more than one chekpoints, the default is to use the last available checkpoint.

Launching the webpage

To launch the web execute the following:

cd ./imgclas/webpage
python serve.py

and it will start running at http://127.0.0.1:5000. To run the webpage in production mode you can pip-install the gunicorn module as an easy drop-in replacement. Once installed just run

cd ./imgclas/webpage
gunicorn serve:app -b 0.0.0.0:80 --workers 1 --timeout 80 -k gevent

Beware of the number of workers because you might get OUT_OF_MEMORY errors if using gpu.

Using the API

You can query your webpage also through an API. You have to make a POST request with the images belonging to your observation.

Python snippets

Here are some Python snippets using the requests module.

Classifying URLs

im_list = ['https://public-media.smithsonianmag.com/filer/89/47/8947cd5c-ac01-4c0e-891a-505517cc0663/istock-540753808.jpg', 
           'https://cdn.pixabay.com/photo/2014/04/10/11/24/red-rose-320868_960_720.jpg']

r = requests.post('http://127.0.0.1:5000/api', data={'mode':'url', 'url_list':im_list})

Classifying local images

im_paths = ['/home/ignacio/image_recognition/data/demo-images/image1.jpg',
            '/home/ignacio/image_recognition/data/demo-images/image2.jpg']

im_names = [str(i) for i in range(len(im_paths))]
im_files = [open(f, 'rb') for f in im_paths]
file_dict = dict(zip(im_names, im_files))

r = requests.post('http://127.0.0.1:5000/api', data={'mode':'localfile'}, files=file_dict)

CURL snippets

Classifying URLs

curl --data "mode=url&url_list=https://public-media.smithsonianmag.com/filer/89/47/8947cd5c-ac01-4c0e-891a-505517cc0663/istock-540753808.jpg&url_list=https://cdn.pixabay.com/photo/2014/04/10/11/24/red-rose-320868_960_720.jpg" http://127.0.0.1:5000/api

Classifying local images

curl --form mode=localfile --form 0=@/home/ignacio/image_recognition/data/demo-images/image1.jpg --form 1=@/home/ignacio/image_recognition/data/demo-images/image2.jpg http://deep.ifca.es/api

Responses

A successful response should return a json, with the labels and their respective probabilities, like the following

{'predictions': [{'info': {'links': {'Google images': 'https://www.google.es/search?tbm=isch&q=Genus+Chenopodium',
                                     'Wikipedia': 'https://en.wikipedia.org/wiki/Genus_Chenopodium'},
                           'metadata': '516 images in DB'},
                  'label': 'Genus Chenopodium',
                  'label_id': 118,
                  'probability': 0.01801883988082409},
                  
                 {'info': {'links': {'Google images': 'https://www.google.es/search?tbm=isch&q=Genus+Rumex',
                                     'Wikipedia': 'https://en.wikipedia.org/wiki/Genus_Rumex'},
                           'metadata': '456 images in DB'},
                  'label': 'Genus Rumex',
                  'label_id': 409,
                  'probability': 0.016028326004743576},
                  
                 {'info': {'links': {'Google images': 'https://www.google.es/search?tbm=isch&q=Genus+Sinapis',
                                     'Wikipedia': 'https://en.wikipedia.org/wiki/Genus_Sinapis'},
                           'metadata': '394 images in DB'},
                  'label': 'Genus Sinapis',
                  'label_id': 435,
                  'probability': 0.013632828369736671},
                  
                 {'info': {'links': {'Google images': 'https://www.google.es/search?tbm=isch&q=Genus+Carex',
                                     'Wikipedia': 'https://en.wikipedia.org/wiki/Genus_Carex'},
                           'metadata': '305 images in DB'},
                  'label': 'Genus Carex',
                  'label_id': 104,
                  'probability': 0.010641136206686497},
                  
                 {'info': {'links': {'Google images': 'https://www.google.es/search?tbm=isch&q=Genus+Sorghum',
                                     'Wikipedia': 'https://en.wikipedia.org/wiki/Genus_Sorghum'},
                           'metadata': '302 images in DB'},
                  'label': 'Genus Sorghum',
                  'label_id': 443,
                  'probability': 0.010484464466571808}],
                  
 'status': 'ok'}