예제 #1
0
파일: train.py 프로젝트: ratatatata/ML-OSM
        # iterate over different patch_offsets
        for patch_offset in HYPERPARAMETERS_OPTIONS["patch_offset"]:
            hyperparameters["patch_offset"] = patch_offset
            print "HYPERPARAMETER: patch_offset = " + str(patch_offset)

            # generate patches
            print "---------------------"
            print "## generating patches from '" + IMG_NAME + "' (" + str(IMG_SIZE[0]) + "x" + str(
                IMG_SIZE[1]
            ) + "; " + str(IMG_BBOX) + ")"
            patch_generator.generate_patches(
                IMG_BBOX,
                IMG_SIZE,
                patch_size=hyperparameters["patch_size"],
                offset_steps=hyperparameters["patch_offset"],
                target_folder=DATASET_DIR,
                force_refresh=False,
                data_folder=IMG_NAME,
            )
            print ""

            # iterate over different codebook_sizes
            dataset_split = 0
            for codebook_size in HYPERPARAMETERS_OPTIONS["codebook_size"]:
                hyperparameters["codebook_size"] = codebook_size
                print "HYPERPARAMETER: codebook_size = " + str(codebook_size)

                # undo dataset splitting
                if dataset_split:
                    all_files = algo.get_imgfiles(TRAININGSET_DIR)
예제 #2
0
def get_imgfiles(path):
    all_files = []
    all_files.extend([join(path, basename(fname)).replace("\\","/")
                    for fname in glob(path + "/*")
                    if splitext(fname)[-1].lower() in EXTENSIONS])
    return all_files



if __name__ == '__main__':
    import patch_generator

    patch_generator.generate_patches(BBOX, DOP_SIZE,
        patch_size=PATCH_SIZE,
        offset_steps=PATCH_OFFSET_STEPS,
        target_folder=DATASETPATH,
        data_folder='dop' + f,
        force_refresh=False
    )


    try:
        os.makedirs(TMP_DIR)
    except:
        None

    algo.__clear_dir(TMP_DIR)

    cats = [0,1]
    ncats = len(cats)