Esempio n. 1
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def image_with_bbox(image, bbox, bbox_ids=None, colors=None, thickness=1, width=None, level=None):

    rgb_image = med2rgb(image, width=width, level=level)

    if bbox_ids is not None and len(bbox_ids) != len(bbox):
        raise ValueError('bbox_ids should have same length as bbox')

    bbox_ids = bbox_ids or list(range(len(bbox)))
    colors = colors or generate_rand_color(n_color=np.max(bbox_ids)+1)

    for i, (x, y, w, h) in enumerate(bbox):
        rgb_image = cv2.rectangle(rgb_image, pt1=(x, y), pt2=(x+w, y+h), color=colors[bbox_ids[i]], thickness=thickness)
    return rgb_image
Esempio n. 2
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def image_with_heatmap(image,
                       heatmap,
                       alpha=0.8,
                       beta=0.3,
                       colormap=cv2.COLORMAP_JET,
                       width=None,
                       level=None):
    rgb_image = med2rgb(image, width=width, level=level)
    uint8_heatmap = np.uint8((heatmap - np.min(heatmap)) /
                             (np.max(heatmap) - np.min(heatmap) + 1e-5) * 255)
    color_heatmap = cv2.applyColorMap(src=uint8_heatmap, colormap=colormap)
    return cv2.addWeighted(src1=rgb_image,
                           alpha=alpha,
                           src2=color_heatmap,
                           beta=beta,
                           gamma=0)
Esempio n. 3
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File: seg.py Progetto: szuboy/medcv
def image_with_mask(image, mask, alpha=0.5, colors=None, width=None, level=None):

    rgb_image = med2rgb(image, width=width, level=level)

    mask = np.squeeze(mask)
    if len(np.shape(mask)) != 2:
        raise ValueError('mask image should have rank 2, but received input shape: %s' % len(np.shape(mask)))

    mask_unique = np.unique(mask)
    mask_labels = mask_unique[np.nonzero(mask_unique)]
    if np.size(mask_labels) < 1:
        raise ValueError('mask must have nonzero label')

    colors = colors or generate_rand_color(n_color=np.size(mask_labels))

    for i, label in enumerate(mask_labels):
        for c in range(3):
            rgb_image[:, :, c] = np.where(mask == label, rgb_image[:, :, c] * (1 - alpha) + colors[i][c] * alpha, rgb_image[:, :, c])
    return rgb_image
Esempio n. 4
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File: seg.py Progetto: szuboy/medcv
def image_with_contours(image, mask, colors=None, thickness=1, width=None, level=None):

    rgb_image = med2rgb(image, width=width, level=level)

    mask = np.squeeze(mask)
    if len(np.shape(mask)) != 2:
        raise ValueError('mask image should have rank 2, but received input shape: %s' % len(np.shape(mask)))

    mask_unique = np.unique(mask)
    mask_labels = mask_unique[np.nonzero(mask_unique)]
    if np.size(mask_labels) < 1:
        raise ValueError('mask must have nonzero label')

    colors = colors or generate_rand_color(n_color=np.size(mask_labels))

    for i, label in enumerate(mask_labels):
        zero_mask = np.zeros_like(mask, dtype=np.uint8)
        zero_mask[mask == label] = 1
        if is_cv3_version:
            _, contours, _ = cv2.findContours(zero_mask, mode=cv2.RETR_TREE, method=cv2.CHAIN_APPROX_NONE)
            rgb_image = cv2.drawContours(rgb_image, contours, contourIdx=-1, color=colors[i], thickness=thickness)
    return rgb_image
Esempio n. 5
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# !/usr/bin/env python
# -*- coding:utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt
from medcv.tools.transform import med2rgb
from medcv.data import chest_dcm, chest_heatmap
from medcv.visualize.cls import image_with_heatmap

# load chest dcm image and its heatmap
chest_dcm_image = chest_dcm()
chest_heatmap_image = chest_heatmap()

# dcm to rgb image with image window width and level
chest_rgb_image = med2rgb(chest_dcm_image, width=22135, level=12209)

# dcm with heatmap
chest_image_with_heatmap = image_with_heatmap(chest_dcm_image,
                                              chest_heatmap_image,
                                              width=22135,
                                              level=12209)

# plot visualize
plt.figure(figsize=(15, 5))
plt.subplot(1, 4, 1)
plt.title('origin image')
plt.imshow(np.squeeze(chest_dcm_image))
plt.subplot(1, 4, 2)
plt.title('rgb image')
plt.imshow(chest_rgb_image)
plt.subplot(1, 4, 3)
Esempio n. 6
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# !/usr/bin/env python
# -*- coding:utf-8 -*-

import matplotlib.pyplot as plt
from medcv.data import chest_dcm
from medcv.tools.transform import med2rgb

# load chest dcm image
chest_dcm_image = chest_dcm()

# width=50000, level=20000
rgb_image1 = med2rgb(chest_dcm_image, width=50000, level=20000)

# width=20000, level=15000
rgb_image2 = med2rgb(chest_dcm_image, width=20000, level=15000)

# width=20000, level=15000, invert=True
rgb_image3 = med2rgb(chest_dcm_image, width=20000, level=15000, invert=True)

# plot visualize
plt.figure(figsize=(15, 5))
plt.subplot(1, 4, 1)
plt.title('chest origin image')
plt.imshow(med2rgb(chest_dcm_image))
plt.subplot(1, 4, 2)
plt.title('width=70000,level=20000')
plt.imshow(rgb_image1)
plt.subplot(1, 4, 3)
plt.title('width=20000,level=15000')
plt.imshow(rgb_image2)
plt.subplot(1, 4, 4)