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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as matio
import os
import cv2
import torch
import matplotlib.patches as mpatches
from skimage import io
def load_mat(path):
with open(path) as f:
mat = matio.loadmat(f)
return mat
def create_patch(pos):
xy = (pos[0], pos[1])
w = pos[2] - pos[0]
h = pos[3] - pos[1]
return mpatches.Rectangle(xy, w, h, alpha=0.7)
def create_circle(xy):
x = xy[0]
y = xy[1]
return mpatches.Circle((x,y), radius=5)
def rescale_bbox(bbox):
midx = (bbox[0] + bbox[2]) / 2.0
midy = (bbox[1] + bbox[3]) / 2.0
w = bbox[2] - bbox[0]
h = bbox[3] - bbox[1]
s = 1.25
w *= s
h *= s
return [midx - w / 2.0, midy - h / 2.0,
midx + w / 2.0, midy + h / 2.0]
def revert_img(img):
mean=[0.485, 0.456, 0.406]
std=[0.229, 0.224, 0.225]
img = img * std + mean
img *= 255
img = np.clip(img, 0, 255)
return img
def get_max(a1, a2):
return max(np.max(a1), np.max(a2))
def get_min(a1, a2):
return min(np.min(a1), np.min(a2))
fig, ax1 = plt.subplots(figsize=(6,6))
ax1.imshow(heatmap)
p1 = create_patch(p_bbox)
p2 = create_patch(p_corner)
ax1.add_patch(p1)
ax1.add_patch(p2)
fig, ax2 = plt.subplots(figsize=(6,6))
ax2.imshow(heatmap)
c1 = create_circle([p1x, p1y])
c2 = create_circle([p2x, p2y])
ax2.add_patch(c1)
ax2.add_patch(c2)
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