server.py 文件源码

def train_svm():
    data = json.loads(request.data)
    detections = data.get('detections', None)
    image = data.get('image', None)
    positive_crop = data.get('positive_crop', None)
    use_dense_sift = data.get('use_dense_sift', False)
    clustering = data.get('clustering', 'kmeans')
    augment_data = data.get('augment_data', True)

    if not (detections and image and positive_crop):
        return json.dumps({'error': 'Parameters error'})

    image = imread_from_base64(image)
    positive_crop = imread_from_base64(positive_crop)

    SVM_MODEL = train_exemplar_svm_on_sift_features(
        image, positive_crop,
        detections[0], detections[1],
        dense_sift=use_dense_sift,
        clustering=clustering,
        augment_data=augment_data
    )

    return json.dumps({'result': 'Success'})