36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
import numpy as np
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import torch
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from PIL import Image
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from random import randint
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from .point import Point
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def tensor_to_pil(image_tensor: torch.tensor):
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image_np = image_tensor.cpu().numpy()
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image_pil = Image.fromarray((image_np.squeeze(0) * 255).astype(np.uint8))
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return image_pil.convert("RGBA")
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def pil_to_tensor(image_pil: Image):
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image_tensor_out = torch.tensor(
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np.array(image_pil).astype(np.float32) / 255.0)
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return torch.unsqueeze(image_tensor_out, 0)
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def generate_noise(image, point1: Point, point2: Point, padding=0):
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def noise_color(i, j, color_index):
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noise = randint(-64, 64)
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return max(0, min(pixels[i, j][color_index] + noise, 255))
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pixels = image.load()
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for i in range(point1.x - padding, point2.x + padding):
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for j in range(point1.y - padding, point2.y + padding):
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try:
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pixels[i, j] = (
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noise_color(i, j, 0),
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noise_color(i, j, 1),
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noise_color(i, j, 2)
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)
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except IndexError:
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pass
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