sachadee

 with torch.no_grad():
        for idx, (image, _) in enumerate(
            tqdm(loader, desc="Create embeddings matrix", total=len(loader)),
        ):
            embeddings = np.empty([1,512])
            embeddings[int(0) :] = F.normalize(backbone(image.to(device))).cpu()
            image = image[0].permute(1,2,0)
            imgarr = image.cpu().detach().numpy()
            print(imgarr.dtype)
            opencvImage = cv2.cvtColor(imgarr, cv2.COLOR_RGB2BGR)

sachadee

//Function to get to convert to bytes the base64 values from python

function base64ToUint8Array(base64) {
		var binaryString = atob(base64);
		var len = binaryString.length;
		var bytes = new Uint8Array(len);
		for (var i = 0; i < len; i++) {
			bytes[i] = binaryString.charCodeAt(i);
		}
		return bytes;

sachadee

from Crypto.Cipher import AES
from Crypto.Random import get_random_bytes
import base64

def encrypt_aes_gcm(plaintext, key):
    cipher = AES.new(key, AES.MODE_GCM)
    ciphertext, tag = cipher.encrypt_and_digest(plaintext)
    return ciphertext, cipher.nonce, tag

# Example usage

sachadee

inflect
librosa==0.9.2
matplotlib
numpy
Pillow
PyQt5
scikit-learn
scipy
sounddevice
SoundFile==0.10.3.post1