how to visualize demo image?

[garriton]

Dear friend,
how to visualize the segmentation result of custom images？
I run the infererce.py and didn’t get a good result. Like this:

I think there are some faults in my code.

Here is my code:

from mmcv.runner import checkpoint
from mmdet.apis.inference import init_detector,LoadImage, inference_detector
import easymd
import cv2
import random
import colorsys
import numpy as np

def random_colors(N, bright=True):
    brightness = 1.0 if bright else 0.7
    hsv = [(i / float(N), 1, brightness) for i in range(N)]
    colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))
    random.shuffle(colors)
    return colors

def apply_mask(image, mask, color, alpha=0.5):
    for c in range(3):
        image[:, :, c] = np.where(mask == 0,
                                  image[:, :, c],
                                  image[:, :, c] *
                                  (1 - alpha) + alpha * color[c] * 255)
    return image

config = './configs/panformer/panformer_pvtb5_24e_coco_panoptic.py'
#checkpoints = './checkpoints/pseg_r101_r50_latest.pth'
checkpoints = "./checkpoints/panoptic_segformer_pvtv2b5_2x.pth"
img_path = "img_path "
mask_save_path = "save_path"

colors = random_colors(80)

model = init_detector(config,checkpoint=checkpoints)

results = inference_detector(model, [img_path])

img = cv2.imread(img_path)

seg = results['segm'][0]
N = len(seg)

masked_image = img.copy()
for i in range(N):
    color = colors[i]
    masks = np.sum(seg[i], axis=0)
    masked_image = apply_mask(masked_image, masks, color)
    # for mask in seg[i]:
    #     masked_image = apply_mask(masked_image, mask, color)

# cv2.imshow("a", masked_image)

[hzf-hhh]

Dear friend, how to visualize the segmentation result of custom images？ I run the infererce.py and didn’t get a good result. Like this:

I think there are some faults in my code.

Here is my code:

from mmcv.runner import checkpoint
from mmdet.apis.inference import init_detector,LoadImage, inference_detector
import easymd
import cv2
import random
import colorsys
import numpy as np

def random_colors(N, bright=True):
    brightness = 1.0 if bright else 0.7
    hsv = [(i / float(N), 1, brightness) for i in range(N)]
    colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))
    random.shuffle(colors)
    return colors

def apply_mask(image, mask, color, alpha=0.5):
    for c in range(3):
        image[:, :, c] = np.where(mask == 0,
                                  image[:, :, c],
                                  image[:, :, c] *
                                  (1 - alpha) + alpha * color[c] * 255)
    return image

config = './configs/panformer/panformer_pvtb5_24e_coco_panoptic.py'
#checkpoints = './checkpoints/pseg_r101_r50_latest.pth'
checkpoints = "./checkpoints/panoptic_segformer_pvtv2b5_2x.pth"
img_path = "img_path "
mask_save_path = "save_path"

colors = random_colors(80)

model = init_detector(config,checkpoint=checkpoints)

results = inference_detector(model, [img_path])

img = cv2.imread(img_path)

seg = results['segm'][0]
N = len(seg)

masked_image = img.copy()
for i in range(N):
    color = colors[i]
    masks = np.sum(seg[i], axis=0)
    masked_image = apply_mask(masked_image, masks, color)
    # for mask in seg[i]:
    #     masked_image = apply_mask(masked_image, mask, color)

# cv2.imshow("a", masked_image)

您好，我想问下您解决了吗，我使用源代码提供的infererce.py，往inference_detector传入img一直报错，但是用[img]却运行正常，但是还是无法用model.show_result(img, result, out_file='result.jpg')将结果映射到图片上，想问下您是如何解决的

[garriton]

Dear friend, how to visualize the segmentation result of custom images？ I run the infererce.py and didn’t get a good result. Like this:
I think there are some faults in my code.
Here is my code:

from mmcv.runner import checkpoint
from mmdet.apis.inference import init_detector,LoadImage, inference_detector
import easymd
import cv2
import random
import colorsys
import numpy as np

def random_colors(N, bright=True):
    brightness = 1.0 if bright else 0.7
    hsv = [(i / float(N), 1, brightness) for i in range(N)]
    colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))
    random.shuffle(colors)
    return colors

def apply_mask(image, mask, color, alpha=0.5):
    for c in range(3):
        image[:, :, c] = np.where(mask == 0,
                                  image[:, :, c],
                                  image[:, :, c] *
                                  (1 - alpha) + alpha * color[c] * 255)
    return image

config = './configs/panformer/panformer_pvtb5_24e_coco_panoptic.py'
#checkpoints = './checkpoints/pseg_r101_r50_latest.pth'
checkpoints = "./checkpoints/panoptic_segformer_pvtv2b5_2x.pth"
img_path = "img_path "
mask_save_path = "save_path"

colors = random_colors(80)

model = init_detector(config,checkpoint=checkpoints)

results = inference_detector(model, [img_path])

img = cv2.imread(img_path)

seg = results['segm'][0]
N = len(seg)

masked_image = img.copy()
for i in range(N):
    color = colors[i]
    masks = np.sum(seg[i], axis=0)
    masked_image = apply_mask(masked_image, masks, color)
    # for mask in seg[i]:
    #     masked_image = apply_mask(masked_image, mask, color)

# cv2.imshow("a", masked_image)

您好，我想问下您解决了吗，我使用源代码提供的infererce.py，往inference_detector传入img一直报错，但是用[img]却运行正常，但是还是无法用model.show_result(img, result, out_file='result.jpg')将结果映射到图片上，想问下您是如何解决的

I’m sorry, I didn’t get the correct output in the end, so I switched to other repository.