| import os |
| import pickle |
|
|
| from .utils import * |
|
|
| from .oxford_pets import OxfordPets |
| from .dtd import DescribableTextures as DTD |
|
|
| IGNORED = ["BACKGROUND_Google", "Faces_easy"] |
| NEW_CNAMES = { |
| "airplanes": "airplane", |
| "Faces": "face", |
| "Leopards": "leopard", |
| "Motorbikes": "motorbike", |
| } |
|
|
|
|
| class Caltech101(DatasetBase): |
|
|
| dataset_dir = "caltech-101" |
|
|
| def __init__(self, root, num_shots=0, seed=1, subsample_classes='all'): |
| root = os.path.abspath(os.path.expanduser(root)) |
| self.dataset_dir = os.path.join(root, self.dataset_dir) |
| self.image_dir = os.path.join(self.dataset_dir, "101_ObjectCategories") |
| self.split_path = os.path.join(self.dataset_dir, "split_zhou_Caltech101.json") |
| self.split_fewshot_dir = os.path.join(self.dataset_dir, "split_fewshot") |
| mkdir_if_missing(self.split_fewshot_dir) |
|
|
| if os.path.exists(self.split_path): |
| train, val, test = OxfordPets.read_split(self.split_path, self.image_dir) |
| else: |
| train, val, test = DTD.read_and_split_data(self.image_dir, ignored=IGNORED, new_cnames=NEW_CNAMES) |
| OxfordPets.save_split(train, val, test, self.split_path, self.image_dir) |
|
|
| if num_shots >= 1: |
| preprocessed = os.path.join(self.split_fewshot_dir, f"shot_{num_shots}-seed_{seed}.pkl") |
| |
| if os.path.exists(preprocessed): |
| print(f"Loading preprocessed few-shot data from {preprocessed}") |
| with open(preprocessed, "rb") as file: |
| data = pickle.load(file) |
| train, val = data["train"], data["val"] |
| else: |
| train = self.generate_fewshot_dataset(train, num_shots=num_shots) |
| val = self.generate_fewshot_dataset(val, num_shots=min(num_shots, 4)) |
| data = {"train": train, "val": val} |
| print(f"Saving preprocessed few-shot data to {preprocessed}") |
| with open(preprocessed, "wb") as file: |
| pickle.dump(data, file, protocol=pickle.HIGHEST_PROTOCOL) |
|
|
| subsample = subsample_classes |
| train, val, test = OxfordPets.subsample_classes(train, val, test, subsample=subsample) |
|
|
| self.templates = [ |
| lambda c: f"a photo of a {c}.", |
| lambda c: f"a painting of a {c}.", |
| lambda c: f"a plastic {c}.", |
| lambda c: f"a sculpture of a {c}.", |
| lambda c: f"a sketch of a {c}.", |
| lambda c: f"a tattoo of a {c}.", |
| lambda c: f"a toy {c}.", |
| lambda c: f"a rendition of a {c}.", |
| lambda c: f"a embroidered {c}.", |
| lambda c: f"a cartoon {c}.", |
| lambda c: f"a {c} in a video game.", |
| lambda c: f"a plushie {c}.", |
| lambda c: f"a origami {c}.", |
| lambda c: f"art of a {c}.", |
| lambda c: f"graffiti of a {c}.", |
| lambda c: f"a drawing of a {c}.", |
| lambda c: f"a doodle of a {c}.", |
| lambda c: f"a photo of the {c}.", |
| lambda c: f"a painting of the {c}.", |
| lambda c: f"the plastic {c}.", |
| lambda c: f"a sculpture of the {c}.", |
| lambda c: f"a sketch of the {c}.", |
| lambda c: f"a tattoo of the {c}.", |
| lambda c: f"the toy {c}.", |
| lambda c: f"a rendition of the {c}.", |
| lambda c: f"the embroidered {c}.", |
| lambda c: f"the cartoon {c}.", |
| lambda c: f"the {c} in a video game.", |
| lambda c: f"the plushie {c}.", |
| lambda c: f"the origami {c}.", |
| lambda c: f"art of the {c}.", |
| lambda c: f"graffiti of the {c}.", |
| lambda c: f"a drawing of the {c}.", |
| lambda c: f"a doodle of the {c}.", |
| ] |
|
|
| super().__init__(train_x=train, val=val, test=test) |
|
|
