mmpose/projects/pose_anything/tools/visualization.py

90 lines
3.2 KiB
Python

import os
import random
import matplotlib.pyplot as plt
import numpy as np
COLORS = ([255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255,
0], [170, 255,
0], [85, 255,
0], [0, 255, 0],
[0, 255, 85], [0, 255, 170], [0, 255,
255], [0, 170,
255], [0, 85, 255], [0, 0, 255],
[85, 0, 255], [170, 0, 255], [255, 0, 255], [255, 0,
170], [255, 0,
85], [255, 0, 0])
def plot_results(support_img,
query_img,
support_kp,
support_w,
query_kp,
query_w,
skeleton,
initial_proposals,
prediction,
radius=6,
out_dir='./heatmaps'):
img_names = [
img.split('_')[0] for img in os.listdir(out_dir)
if str_is_int(img.split('_')[0])
]
if len(img_names) > 0:
name_idx = max([int(img_name) for img_name in img_names]) + 1
else:
name_idx = 0
h, w, c = support_img.shape
prediction = prediction[-1].cpu().numpy() * h
support_img = (support_img - np.min(support_img)) / (
np.max(support_img) - np.min(support_img))
query_img = (query_img - np.min(query_img)) / (
np.max(query_img) - np.min(query_img))
for index, (img, w, keypoint) in enumerate(
zip([support_img, query_img], [support_w, query_w],
[support_kp, prediction])):
f, axes = plt.subplots()
plt.imshow(img)
for k in range(keypoint.shape[0]):
if w[k] > 0:
kp = keypoint[k, :2]
c = (1, 0, 0, 0.75) if w[k] == 1 else (0, 0, 1, 0.6)
patch = plt.Circle(kp, radius, color=c)
axes.add_patch(patch)
axes.text(kp[0], kp[1], k)
plt.draw()
for limb_index, limb in enumerate(skeleton):
kp = keypoint[:, :2]
if limb_index > len(COLORS) - 1:
c = [x / 255 for x in random.sample(range(0, 255), 3)]
else:
c = [x / 255 for x in COLORS[limb_index]]
if w[limb[0]] > 0 and w[limb[1]] > 0:
patch = plt.Line2D([kp[limb[0], 0], kp[limb[1], 0]],
[kp[limb[0], 1], kp[limb[1], 1]],
linewidth=6,
color=c,
alpha=0.6)
axes.add_artist(patch)
plt.axis('off') # command for hiding the axis.
name = 'support' if index == 0 else 'query'
plt.savefig(
f'./{out_dir}/{str(name_idx)}_{str(name)}.png',
bbox_inches='tight',
pad_inches=0)
if index == 1:
plt.show()
plt.clf()
plt.close('all')
def str_is_int(s):
try:
int(s)
return True
except ValueError:
return False