| import numpy as np
|
| import cv2
|
| import torch
|
| import numpy as np
|
| from PIL import Image
|
|
|
|
|
| def instantiate_from_config(config):
|
| if not "target" in config:
|
| raise KeyError("Expected key `target` to instantiate.")
|
| return get_obj_from_str(config["target"])(**config.get("params", dict()))
|
|
|
|
|
| def get_obj_from_str(string, reload=False):
|
| import importlib
|
| module, cls = string.rsplit(".", 1)
|
| if reload:
|
| module_imp = importlib.import_module(module)
|
| importlib.reload(module_imp)
|
| return getattr(importlib.import_module(module, package=None), cls)
|
|
|
|
|
| def tensor_detail(t):
|
| assert type(t) == torch.Tensor
|
| print(f"shape: {t.shape} mean: {t.mean():.2f}, std: {t.std():.2f}, min: {t.min():.2f}, max: {t.max():.2f}")
|
|
|
|
|
|
|
| def drawRoundRec(draw, color, x, y, w, h, r):
|
| drawObject = draw
|
|
|
| '''Rounds'''
|
| drawObject.ellipse((x, y, x + r, y + r), fill=color)
|
| drawObject.ellipse((x + w - r, y, x + w, y + r), fill=color)
|
| drawObject.ellipse((x, y + h - r, x + r, y + h), fill=color)
|
| drawObject.ellipse((x + w - r, y + h - r, x + w, y + h), fill=color)
|
|
|
| '''rec.s'''
|
| drawObject.rectangle((x + r / 2, y, x + w - (r / 2), y + h), fill=color)
|
| drawObject.rectangle((x, y + r / 2, x + w, y + h - (r / 2)), fill=color)
|
|
|
|
|
| def do_resize_content(original_image: Image, scale_rate):
|
|
|
| if scale_rate != 1:
|
|
|
| new_size = tuple(int(dim * scale_rate) for dim in original_image.size)
|
|
|
| resized_image = original_image.resize(new_size)
|
|
|
| padded_image = Image.new("RGBA", original_image.size, (0, 0, 0, 0))
|
| paste_position = ((original_image.width - resized_image.width) // 2, (original_image.height - resized_image.height) // 2)
|
| padded_image.paste(resized_image, paste_position)
|
| return padded_image
|
| else:
|
| return original_image
|
|
|
| def add_stroke(img, color=(255, 255, 255), stroke_radius=3):
|
|
|
| if isinstance(img, Image.Image):
|
| assert img.mode == "RGBA"
|
| img = cv2.cvtColor(np.array(img), cv2.COLOR_RGBA2BGRA)
|
| else:
|
| assert img.shape[2] == 4
|
| gray = img[:,:, 3]
|
| ret, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
|
| contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
|
| res = cv2.drawContours(img, contours,-1, tuple(color)[::-1] + (255,), stroke_radius)
|
| return Image.fromarray(cv2.cvtColor(res,cv2.COLOR_BGRA2RGBA))
|
|
|
| def make_blob(image_size=(512, 512), sigma=0.2):
|
| """
|
| make 2D blob image with:
|
| I(x, y)=1-\exp \left(-\frac{(x-H / 2)^2+(y-W / 2)^2}{2 \sigma^2 HS}\right)
|
| """
|
| import numpy as np
|
| H, W = image_size
|
| x = np.arange(0, W, 1, float)
|
| y = np.arange(0, H, 1, float)
|
| x, y = np.meshgrid(x, y)
|
| x0 = W // 2
|
| y0 = H // 2
|
| img = 1 - np.exp(-((x - x0) ** 2 + (y - y0) ** 2) / (2 * sigma ** 2 * H * W))
|
| return (img * 255).astype(np.uint8) |
