MarcoParola's picture
add following features: update dropdowns after each rank submission, save the results at the end of the form in the dataset hub
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import os
import pandas as pd
from huggingface_hub import HfApi, HfFolder
import yaml
import numpy as np
import time
config = yaml.safe_load(open("./config/config.yaml"))
def load_image_and_saliency(class_idx, data_dir):
path = os.path.join(data_dir, 'images', str(class_idx))
images = os.listdir(path)
# pick a random image
id = np.random.randint(0, len(images))
image = os.path.join(path, images[id])
gradcam_image = os.path.join(data_dir, 'saliency', 'gradcam', images[id])
lime_image = os.path.join(data_dir, 'saliency', 'lime', images[id])
sidu_image = os.path.join(data_dir, 'saliency', 'sidu', images[id])
rise_image = os.path.join(data_dir, 'saliency', 'rise', images[id])
return image, gradcam_image, lime_image, sidu_image, rise_image
def load_example_images(class_idx, data_dir, max_images=16):
path = os.path.join(data_dir, 'images', str(class_idx))
images = os.listdir(path)
# pick max_images random images
ids = np.random.choice(len(images), max_images, replace=False)
images = [os.path.join(path, images[id]) for id in ids]
return images
# Function to load words based on global variable
def load_words(idx):
words = [f"word_{idx}_{i}" for i in range(20)]
return words