def suite_result(self, suite, result, **kwargs): """ Extended from parent with JSON export functionality :param suite: default testrunner test suite :param result: StoreResultsTestRunner instance """ result.results['results'] = self.get_results_summary( results=result.results) with open(settings.PROJECT_DIR('') + '/test_results.json', 'w') as outfile: json.dump(result.results, outfile, sort_keys=True, indent=4) t = get_template('test/test_results.html') c = Context(result.results) with open(settings.PROJECT_DIR('') + '/test_results.html', 'w') as outfile: outfile.write(t.render(c)) super(ConcreteDiscoverRunner, self).suite_result(suite, result, **kwargs)
def download_pdf(data: pd.DataFrame, file_name='output'): data_html = data.to_html(index=False) try: data_pdf = pdf.from_string(data_html, False) except OSError: env = Environment(loader=FileSystemLoader(settings.PROJECT_DIR('templates'))) template = env.get_template('pdf_export.html') template_vars = {"title": file_name.capitalize(), "table": data_html} data_pdf = HTML(string=template.render(template_vars)).write_pdf() response = HttpResponse(content_type='application/pdf') response['Content-Disposition'] = 'attachment; filename="{}.{}"'.format(file_name, 'pdf') response.write(data_pdf) return response
def process_path(file_path, imf): if file_path: if file_path.startswith(settings.MEDIA_URL): file_path = file_path[1:] file_path = settings.PROJECT_DIR('../{0}'.format(file_path)) files[field_name] = (imf.name, open(file_path, 'rb'))
import numpy as np import os from muses.naive_classification.definitions_os import classes from collections import OrderedDict from keras.models import model_from_json from PIL import Image from django.conf import settings LOADED_MODELS = {} json_path = settings.PROJECT_DIR( os.path.join( '..', '..', '..', 'src', 'muses', 'naive_classification', 'model_architecture.json', )) def predict_image_paths(image_paths, model_path, target_size=(128, 128)): """Use a trained classifier to predict the class probabilities of a list of images Returns most likely class and its probability :param image_paths: list of path(s) to the image(s) :param model_path: path to the pre-trained model :param target_size: :type image_paths: list :return: