示例#1
0
def load_instances(input_filepath, output_filepath, mesh_list, symemtry_part_index):
    dirnames = glob.glob(input_filepath + "/*")

    exp_name = os.path.basename(os.path.normpath(input_filepath + "/../"))
    exp_output_filepath = output_filepath + "/images/" + exp_name
    print (exp_name)
    if not os.path.isdir(output_filepath + "/images/"):
        os.mkdir(output_filepath + "/images/")
    if not os.path.isdir(exp_output_filepath):
        os.mkdir(exp_output_filepath)

    instances = []

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

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

        if not prefix in mesh_list:
            continue

        abs_dirname = os.path.abspath(dirname)

        is_loaded = True

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

        absolute_image_filepath = []
        image_filenames = []
        # image_filenames.append(prefix + '_view.png')
        image_filenames.append(prefix + "_input.png")

        image_filenames.append("../../part_assembly/" + prefix + "/" + prefix + "_assembly_cuboid.png")
        image_filenames.append("../../part_assembly/" + prefix + "/" + prefix + "_assembly_accuracy.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, exp_output_filepath)

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

            # Get relative file path.
            # absolute_image_filepath.append(abs_dirname + '/' + image_filename)
            absolute_image_filepath.append("images/" + exp_name + "/" + os.path.basename(image_filename))

        if not is_loaded:
            continue

        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"

            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,
            absolute_image_filepath[0],
            absolute_image_filepath[1],
            absolute_image_filepath[2],
            absolute_image_filepath[3],
            absolute_image_filepath[4],
            # absolute_image_filepath[5],
            # absolute_image_filepath[6],
            # absolute_image_filepath[7],
            # absolute_image_filepath[8],
            # accuracy_values[0], completeness_values[0],
            # accuracy_values[1], completeness_values[1],
            # accuracy_values[2], completeness_values[2]
        )

        instances.append(instance)

    return instances
示例#2
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

        abs_dirname = os.path.abspath(dirname)

        is_loaded = True

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

        absolute_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.
            absolute_image_filepath.append(abs_dirname + '/' + image_filename)

        if not is_loaded:
            continue

        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'

            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, absolute_image_filepath[0],
                                  absolute_image_filepath[1], absolute_image_filepath[2],
                                  absolute_image_filepath[3], absolute_image_filepath[4],
                                  absolute_image_filepath[5], absolute_image_filepath[6],
                                  absolute_image_filepath[7], absolute_image_filepath[8],
                                  accuracy_values[0], completeness_values[0],
                                  accuracy_values[1], completeness_values[1],
                                  accuracy_values[2], completeness_values[2])

        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):
    dirnames = glob.glob(input_filepath + '/*')

    all_accu_values = [[], [], [], [], []]
    all_comp_values = [[], [], [], [], []]
    x_values = []
    count_instances = 0

    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))

        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 is_loaded:
            continue

        csv_filename_postfixes = []
        csv_filename_postfixes.append(prefix + '_' + str(candidate_index) + '_symmetry')
        csv_filename_postfixes.append(prefix + '_' + str(candidate_index) + '_database')
        csv_filename_postfixes.append(prefix + '_' + str(candidate_index) + '_fusion')
        csv_filename_postfixes.append('/../../part_assembly/' + prefix + '/' + prefix +'_assembly')
        csv_filename_postfixes.append('/../../symmetry_detection/' + prefix + '/' + prefix +'_symm_detection_recon')

        file_exist = True
        for i in range(len(csv_filename_postfixes)):
            csv_filename_postfix = csv_filename_postfixes[i]
            csv_filename = dirname + '/' + csv_filename_postfix + '.csv'
            if not os.path.isfile(csv_filename):
                file_exist = False
                break

        if not file_exist:
            continue

        for i in range(len(csv_filename_postfixes)):
            csv_filename_postfix = csv_filename_postfixes[i]
            csv_filename = dirname + '/' + csv_filename_postfix + '.csv'
            if not os.path.isfile(csv_filename):
                continue

            (accu_values, comp_values, x_values) = librr.get_csv_all_value(csv_filename)

            if not all_accu_values[i]:
                all_accu_values[i] = accu_values
            if not all_comp_values[i]:
                all_comp_values[i] = comp_values
                
            all_accu_values[i] = [x+y for x,y in zip(all_accu_values[i], accu_values)]
            all_comp_values[i] = [x+y for x,y in zip(all_comp_values[i], comp_values)]

        count_instances += 1

    if count_instances > 0:
        for i in range(len(all_accu_values)):
            all_accu_values[i] = [x / count_instances for x in all_accu_values[i]]
        for i in range(len(all_comp_values)):
            all_comp_values[i] = [x / count_instances for x in all_comp_values[i]]

    return (all_accu_values, all_comp_values, x_values)
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):

    output_file_prefix = os.path.basename(os.path.normpath(input_filepath + '/../'))

    dirnames = glob.glob(input_filepath + '/*')

    print(output_file_prefix + '_ours.csv')
    print(output_file_prefix + '_podolak.csv')

    ours_file = open(output_file_prefix + '_ours.csv', 'w')
    podolak_file = open(output_file_prefix + '_podolak.csv', 'w')
    
    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))

        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

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

        if not is_loaded:
            continue

        ours_symm_filename_postfix = '_' + str(candidate_index) + '_symmetry_info.txt'
        ours_symm_filename = dirname + '/' + prefix + ours_symm_filename_postfix

        if os.path.exists(ours_symm_filename):
            with open(ours_symm_filename, 'r') as csv_file:
                data = csv.reader(csv_file, delimiter=',')
                x_data = data.next()
                n = np.array([float(x_data[1]), float(x_data[2]), float(x_data[3])])
                t = float(x_data[4])
                n = n / np.linalg.norm(n)
                ours_file.write(str(n[0]) + ',' + str(n[1]) + ',' + str(n[2]) + ',' + str(t) + '\n')

        podolak_symm_filename_postfix = '_symmetry_info.txt'
        podolak_symm_filename = dirname + '/../../symmetry_detection/' + prefix + '/' + prefix + podolak_symm_filename_postfix
        print(podolak_symm_filename)

        if os.path.exists(podolak_symm_filename):
            with open(podolak_symm_filename, 'r') as csv_file:
                data = csv.reader(csv_file, delimiter=',')
                x_data = data.next()
                n = np.array([float(x_data[1]), float(x_data[2]), float(x_data[3])])
                t = float(x_data[4])
                n = n / np.linalg.norm(n)
                podolak_file.write(str(n[0]) + ',' + str(n[1]) + ',' + str(n[2]) + ',' + str(t) + '\n')

    ours_file.close()
    podolak_file.close()