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on
Zero
Running
on
Zero
import os | |
import json | |
import pickle | |
import random | |
import time | |
import itertools | |
import numpy as np | |
from PIL import Image | |
import skimage.io as io | |
import matplotlib.pyplot as plt | |
from matplotlib.collections import PatchCollection | |
from matplotlib.patches import Polygon, Rectangle | |
from torch.utils.data import Dataset | |
import webdataset as wds | |
from minigpt4.datasets.datasets.base_dataset import BaseDataset | |
from minigpt4.datasets.datasets.caption_datasets import CaptionDataset | |
class CoTDataset(Dataset): | |
def __init__(self, text_processor, ann_path): | |
""" | |
vis_root (string): Root directory of images (e.g. coco/images/) | |
ann_root (string): directory to store the annotation file | |
""" | |
self.text_processor = text_processor | |
with open(ann_path, 'r') as f: | |
self.ann = json.load(f) | |
def __len__(self): | |
return len(self.ann) | |
def __getitem__(self, index): | |
info = self.ann[index] | |
input = info["inputs"] | |
target = info["targets"] | |
return { | |
"instruction_input": input, | |
"answer": target, | |
} | |