| import base64
|
|
|
| from xml.dom import minidom
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| import cv2
|
| import numpy as np
|
| from czifile import CziFile
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| from tifffile import imread
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|
|
|
|
| def read_svg(svg_path):
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| doc = minidom.parse(str(svg_path))
|
| img_strings = {
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| path.getAttribute("id"): path.getAttribute("href")
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| for path in doc.getElementsByTagName("image")
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| }
|
| doc.unlink()
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|
|
| red = img_strings["Red"]
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| green = img_strings["Green"]
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| red = base64.b64decode(red.split(",")[1])
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| green = base64.b64decode(green.split(",")[1])
|
| red = cv2.imdecode(np.frombuffer(red, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
|
| green = cv2.imdecode(np.frombuffer(green, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
|
|
|
| red = cv2.cvtColor(red, cv2.COLOR_BGRA2GRAY)
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| green = cv2.cvtColor(green, cv2.COLOR_BGRA2GRAY)
|
| mask = np.zeros_like(red)
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| mask[red > 0] = 1
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| mask[green > 0] = 2
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| return mask
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|
|
|
|
| def extract_bboxes(mask):
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| mask = np.array(mask)
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| mask = mask.astype(np.uint8)
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|
|
|
|
| num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(
|
| mask, connectivity=8
|
| )
|
| bboxes = []
|
| for i in range(1, num_labels):
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| x, y, w, h, area = stats[i]
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| bboxes.append([x, y, x + w, y + h])
|
| return bboxes
|
|
|
|
|
| def preprocess(raw_data, reverse_channels=False):
|
| MAX_VALUE = 2**16 - 1
|
| if raw_data.ndim == 2:
|
| raw_data = raw_data[np.newaxis, :, :]
|
| h, w = raw_data.shape[1:3]
|
| orders = np.arange(raw_data.shape[0])[::-1]
|
| result = np.zeros((h, w, 3), dtype=np.uint8)
|
|
|
| for i, chan in enumerate(raw_data):
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| hist, bins = np.histogram(chan.ravel(), MAX_VALUE + 1, (0, MAX_VALUE + 1))
|
| cdf = hist.cumsum()
|
| cdf_normalized = cdf / cdf[-1]
|
| bmax = np.searchsorted(cdf_normalized, 0.99, side="left")
|
| clip = np.clip(chan, 0, bmax).astype(np.float32)
|
| clip = (clip - clip.min()) / (bmax - clip.min()) * 255
|
| result[:, :, orders[i]] = clip
|
| if reverse_channels:
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|
|
| result = result[:, :, [1, 0, 2]]
|
| return result
|
|
|
|
|
| def read_czi(filepath):
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| data = CziFile(filepath)
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|
|
| return data.asarray().squeeze()
|
|
|
|
|
| def read_tiff(filepath):
|
|
|
| data = imread(filepath).squeeze()
|
|
|
| return data |
