Пример #1
0
def load_instances(input_filepath, output_filepath, symemtry_part_index):
    dirnames = glob.glob(input_filepath + '/*')

    instances = []

    for dirname in dirnames:
        if not os.path.isdir(dirname):
            continue

        prefix = os.path.basename(dirname)
        print prefix

        is_loaded = True

        relative_image_filepath = []
        image_filenames = []
        image_filenames.append(prefix + '_view.png')
        image_filenames.append(prefix + '_input.png')
        image_filenames.append(prefix + '_symm_detection_recon.png')
        image_filenames.append(prefix + '_symm_detection_accuracy.png')
        image_filenames.append(prefix + '_symm_detection_completeness.png')

        # FIXME
        if not os.path.exists(dirname + '/../../output/' + prefix + '/' +
                              prefix + '_input.png'):
            continue
        if not os.path.exists(dirname + '/../../output/' + prefix + '/' +
                              prefix + '_view.png'):
            continue

        shutil.copy(
            dirname + '/../../output/' + prefix + '/' + prefix + '_input.png',
            dirname + '/' + prefix + '_input.png')
        shutil.copy(
            dirname + '/../../output/' + prefix + '/' + prefix + '_view.png',
            dirname + '/' + prefix + '_view.png')

        for image_filename in image_filenames:
            if not os.path.exists(dirname + '/' + image_filename):
                print 'Warning: File does not exist: "' + (
                    dirname + '/' + image_filename) + '"'
                is_loaded = False
                break

            if not os.path.exists(output_filepath + '/' + image_filename):
                # Copy the image.
                shutil.copy(dirname + '/' + image_filename, output_filepath)

                # Create a thumbnail.
                librr.create_thumbnails(output_filepath + '/' + image_filename,
                                        librr.thumbname_width)

            # Get relative file path.
            relative_image_filepath.append('./' + image_filename)

        if not is_loaded:
            continue

        accuracy_values = []
        completeness_values = []
        csv_filename_postfixes = []
        csv_filename_postfixes.append('_symm_detection_recon')

        for csv_filename_postfix in csv_filename_postfixes:
            csv_filename = dirname + '/' + prefix + csv_filename_postfix + '.csv'
            if symemtry_part_index >= 0:
                # Real per-part files.
                csv_filename = dirname + '/' + prefix + csv_filename_postfix\
                               + '_' + str(symemtry_part_index) + '.csv'

            all_values = librr.get_csv_value(csv_filename, librr.threshold)

            if not all_values:
                accuracy_values.append(float("NaN"))
                completeness_values.append(float("NaN"))
            else:
                accuracy_values.append(all_values[0])
                completeness_values.append(all_values[1])

        instance = OutputInstance(prefix, relative_image_filepath[0],
                                  relative_image_filepath[1],
                                  relative_image_filepath[2],
                                  relative_image_filepath[3],
                                  relative_image_filepath[4],
                                  accuracy_values[0], completeness_values[0])

        instances.append(instance)

    return instances
def load_instances(input_filepath, output_filepath, symemtry_part_index):
    dirnames = glob.glob(input_filepath + '/*')

    instances = []

    for dirname in dirnames:
        if not os.path.isdir(dirname):
            continue

        prefix = os.path.basename(dirname)
        print prefix

        is_loaded = True

        candidate_index = librr.find_best_candidate(dirname, prefix)
        print('Candidate index: ' + str(candidate_index))

        # Read images.
        relative_image_filepath = []
        image_filenames = []
        image_filenames.append(prefix + '_view.png')
        image_filenames.append(prefix + '_input.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_symmetry_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_symmetry_completeness.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_database_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_database_completeness.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_fusion_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) +
                               '_fusion_completeness.png')

        for image_filename in image_filenames:
            if not os.path.exists(dirname + '/' + image_filename):
                print 'Warning: File does not exist: "' + (
                    dirname + '/' + image_filename) + '"'
                is_loaded = False
                break

            if not os.path.exists(output_filepath + '/' + image_filename):
                # Copy the image.
                shutil.copy(dirname + '/' + image_filename, output_filepath)

                # Create a thumbnail.
                librr.create_thumbnails(output_filepath + '/' + image_filename,
                                        librr.thumbname_width)

            # Get relative file path.
            relative_image_filepath.append('./' + image_filename)

        if not is_loaded:
            continue

        # Read stats.
        accuracy_values = []
        completeness_values = []
        csv_filename_postfixes = []
        csv_filename_postfixes.append('_' + str(candidate_index) + '_symmetry')
        csv_filename_postfixes.append('_' + str(candidate_index) + '_database')
        csv_filename_postfixes.append('_' + str(candidate_index) + '_fusion')

        for csv_filename_postfix in csv_filename_postfixes:
            csv_filename = dirname + '/' + prefix + csv_filename_postfix + '.csv'
            if symemtry_part_index >= 0:
                # Read per-part files.
                csv_filename = dirname + '/' + prefix + csv_filename_postfix\
                               + '_' + str(symemtry_part_index) + '.csv'

            if not os.path.exists(csv_filename):
                print 'Warning: File does not exist: "' + csv_filename + '"'
                is_loaded = False
                break
            else:
                all_values = librr.get_csv_value(csv_filename, librr.threshold)
                if not all_values:
                    accuracy_values.append(float("NaN"))
                    completeness_values.append(float("NaN"))
                else:
                    accuracy_values.append(all_values[0])
                    completeness_values.append(all_values[1])

        if not is_loaded:
            continue

        # Read per-point labeling accuracy.
        csv_filename = dirname + '/' + prefix + '_' + str(
            candidate_index) + '_labeling_stats.csv'
        if not os.path.exists(csv_filename):
            print 'Warning: File does not exist: "' + csv_filename + '"'
            continue
        else:
            per_point_labeling_accuracy = read_value_from_csv_file(
                csv_filename, symemtry_part_index, 3)

        # Read cuboid distance to ground truth.
        csv_filename = dirname + '/' + prefix + '_' + str(
            candidate_index) + '_cuboid_distance.csv'
        if not os.path.exists(csv_filename):
            print 'Warning: File does not exist: "' + csv_filename + '"'
            continue
        else:
            cuboid_distance_to_ground_truth = read_value_from_csv_file(
                csv_filename, symemtry_part_index, 1)

        instance = OutputInstance(
            prefix, relative_image_filepath[0], relative_image_filepath[1],
            relative_image_filepath[2], relative_image_filepath[3],
            relative_image_filepath[4], relative_image_filepath[5],
            relative_image_filepath[6], relative_image_filepath[7],
            relative_image_filepath[8], accuracy_values[0],
            completeness_values[0], accuracy_values[1], completeness_values[1],
            accuracy_values[2], completeness_values[2],
            per_point_labeling_accuracy, cuboid_distance_to_ground_truth)

        instances.append(instance)

    return instances
def load_instances(input_filepath, output_filepath, symemtry_part_index):
    dirnames = glob.glob(input_filepath + '/*')

    instances = []

    for dirname in dirnames:
        if not os.path.isdir(dirname):
            continue

        prefix = os.path.basename(dirname)
        print prefix

        is_loaded = True

        relative_image_filepath = []
        image_filenames = []
        #image_filenames.append(prefix + '_view.png')
        #image_filenames.append(prefix + '_input.png')
        #image_filenames.append(prefix + '_symm_detection_recon.png')
        #image_filenames.append(prefix + '_symm_detection_accuracy.png')
        #image_filenames.append(prefix + '_symm_detection_completeness.png')


        for image_filename in image_filenames:
            if not os.path.exists(dirname + '/' + image_filename):
                print 'Warning: File does not exist: "' + (dirname + '/' + image_filename) + '"'
                is_loaded = False
                break

            if not os.path.exists(output_filepath + '/' + image_filename):
                # Copy the image.
                shutil.copy(dirname + '/' + image_filename, output_filepath)

                # Create a thumbnail.
                librr.create_thumbnails(output_filepath + '/' + image_filename, librr.thumbname_width)

            # Get relative file path.
            relative_image_filepath.append('./' + image_filename)

        if not is_loaded:
            continue

        accuracy_values = []
        completeness_values = []
        csv_filename_postfixes = []
        csv_filename_postfixes.append('_baseline')

        for csv_filename_postfix in csv_filename_postfixes:
            csv_filename = dirname + '/' + prefix + csv_filename_postfix + '.csv'
            if symemtry_part_index >= 0:
            # Real per-part files.
                csv_filename = dirname + '/' + prefix + csv_filename_postfix\
                               + '_' + str(symemtry_part_index) + '.csv'

            all_values = librr.get_csv_value(csv_filename, librr.threshold)

            if not all_values:
                print('Warning: NaN values (' + prefix + ')')
                accuracy_values.append(float("NaN"))
                completeness_values.append(float("NaN"))
            else:
                accuracy_values.append(all_values[0])
                completeness_values.append(all_values[1])

        instance = OutputInstance(prefix, #relative_image_filepath[0], relative_image_filepath[1], relative_image_filepath[2],
                                  #relative_image_filepath[3], relative_image_filepath[4],
                                  accuracy_values[0], completeness_values[0])

        instances.append(instance)

    return instances
def load_instances(input_filepath, output_filepath, symemtry_part_index):
    dirnames = glob.glob(input_filepath + '/*')

    instances = []

    for dirname in dirnames:
        if not os.path.isdir(dirname):
            continue

        prefix = os.path.basename(dirname)
        print prefix

        is_loaded = True

        candidate_index = librr.find_best_candidate(dirname, prefix)
        print('Candidate index: ' + str(candidate_index))

        # Read images.
        relative_image_filepath = []
        image_filenames = []
        image_filenames.append(prefix + '_view.png')
        image_filenames.append(prefix + '_input.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_symmetry_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_symmetry_completeness.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_database_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_database_completeness.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_fusion_accuracy.png')
        image_filenames.append(prefix + '_' + str(candidate_index) + '_fusion_completeness.png')

        for image_filename in image_filenames:
            if not os.path.exists(dirname + '/' + image_filename):
                print 'Warning: File does not exist: "' + (dirname + '/' + image_filename) + '"'
                is_loaded = False
                break

            if not os.path.exists(output_filepath + '/' + image_filename):
                # Copy the image.
                shutil.copy(dirname + '/' + image_filename, output_filepath)

                # Create a thumbnail.
                librr.create_thumbnails(output_filepath + '/' + image_filename, librr.thumbname_width)

            # Get relative file path.
            relative_image_filepath.append('./' + image_filename)

        if not is_loaded:
            continue

        # Read stats.
        accuracy_values = []
        completeness_values = []
        csv_filename_postfixes = []
        csv_filename_postfixes.append('_' + str(candidate_index) + '_symmetry')
        csv_filename_postfixes.append('_' + str(candidate_index) + '_database')
        csv_filename_postfixes.append('_' + str(candidate_index) + '_fusion')

        for csv_filename_postfix in csv_filename_postfixes:
            csv_filename = dirname + '/' + prefix + csv_filename_postfix + '.csv'
            if symemtry_part_index >= 0:
                # Read per-part files.
                csv_filename = dirname + '/' + prefix + csv_filename_postfix\
                               + '_' + str(symemtry_part_index) + '.csv'

            if not os.path.exists(csv_filename):
                print 'Warning: File does not exist: "' + csv_filename + '"'
                is_loaded = False
                break
            else:
                all_values = librr.get_csv_value(csv_filename, librr.threshold)
                if not all_values:
                    accuracy_values.append(float("NaN"))
                    completeness_values.append(float("NaN"))
                else:
                    accuracy_values.append(all_values[0])
                    completeness_values.append(all_values[1])

        if not is_loaded:
            continue

        # Read per-point labeling accuracy.
        csv_filename = dirname + '/' + prefix + '_' + str(candidate_index) + '_labeling_stats.csv'
        if not os.path.exists(csv_filename):
            print 'Warning: File does not exist: "' + csv_filename + '"'
            continue
        else:
            per_point_labeling_accuracy = read_value_from_csv_file(csv_filename, symemtry_part_index, 3)

        # Read cuboid distance to ground truth.
        csv_filename = dirname + '/' + prefix + '_' + str(candidate_index) + '_cuboid_distance.csv'
        if not os.path.exists(csv_filename):
            print 'Warning: File does not exist: "' + csv_filename + '"'
            continue
        else:
            cuboid_distance_to_ground_truth = read_value_from_csv_file(csv_filename, symemtry_part_index, 1)

        instance = OutputInstance(prefix, relative_image_filepath[0],
                                  relative_image_filepath[1], relative_image_filepath[2],
                                  relative_image_filepath[3], relative_image_filepath[4],
                                  relative_image_filepath[5], relative_image_filepath[6],
                                  relative_image_filepath[7], relative_image_filepath[8],
                                  accuracy_values[0], completeness_values[0],
                                  accuracy_values[1], completeness_values[1],
                                  accuracy_values[2], completeness_values[2],
                                  per_point_labeling_accuracy, cuboid_distance_to_ground_truth)

        instances.append(instance)

    return instances