Generate CLAHE-applied + resized Image for Sorghum -100 Cultivar Identification - FGVC 9

gen.py

import os
import torch
from torchvision import transforms as T
import PIL
import numpy as np
import cv2

def tensor2np(tensor):
    return tensor.permute(1, 2, 0).numpy().astype(np.uint8)

def np2tensor(nparr):
    return torch.tensor(nparr).permute(2, 0, 1).float()

def CLAHE(image):
    hsv = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)
    clahe = cv2.createCLAHE(clipLimit=10)
    hsv[:,:,-1] = clahe.apply(hsv[:,:,-1])
    rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB)
    return rgb

def makedirs(path):
    if not os.path.exists(path):
        os.makedirs(path)
        
################################################################

root_dir = os.path.join('./x')
out_dir = os.path.join('./outputs')

TARGET_WIDTH_HEIGHT = 256

transform = T.Compose([
    np.array,
    CLAHE,
    np2tensor,
    T.Resize(TARGET_WIDTH_HEIGHT),
    tensor2np,
])

makedirs(root_dir)

for root, dirs, files in os.walk(root_dir):
    for f in files:
        in_path = os.path.join(root, f)
        out_dir_path = os.path.join(out_dir, root)
        out_path = os.path.join(out_dir_path, f)
        makedirs(out_dir_path)

        pil_image = PIL.Image.open(in_path)
        np_image = transform(pil_image)
        pil_image_out = PIL.Image.fromarray(np_image)
        pil_image_out.save(out_path, 'png')
        print(in_path, '->', out_path)

Before

After