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cnn-model

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jishanshanss
jishanshanss commented Apr 26, 2020

original code :

img = ori_img.astype(np.float)/255.
img = cv2.resize(img, self.size)
img = torch.from_numpy(img).float().permute(2,0,1).unsqueeze(0)
img = img.to(self.device)
with torch.no_grad():
            out_boxes = self.net(img)

I suggest using:

from PIL import Image
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
from torch.au

An Image classifier to identify whether the given image is Batman or Superman using a CNN with high accuracy. (From getting images from google to saving our trained model for reuse.)

  • Updated Dec 8, 2019
  • Python

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

  • Updated Jan 19, 2020
  • Python

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