def plot_polygon(polygon,
color=None,
draw_labels=True,
label_direction=1,
indexing="xy",
axis=None):
if python_utils.module_exists("matplotlib.pyplot"):
import matplotlib.pyplot as plt
if axis is None:
axis = plt.gca()
polygon_closed = np.append(polygon, [polygon[0, :]], axis=0)
if indexing == "xy=":
axis.plot(polygon_closed[:, 0],
polygon_closed[:, 1],
color=color,
linewidth=3.0)
elif indexing == "ij":
axis.plot(polygon_closed[:, 1],
polygon_closed[:, 0],
color=color,
linewidth=3.0)
else:
print("WARNING: Invalid indexing argument")
if draw_labels:
labels = range(1, polygon.shape[0] + 1)
for label, x, y in zip(labels, polygon[:, 0], polygon[:, 1]):
axis.annotate(label,
xy=(x, y),
xytext=(-20 * label_direction,
20 * label_direction),
textcoords='offset points',
ha='right',
va='bottom',
bbox=dict(boxstyle='round,pad=0.25',
fc=color,
alpha=0.75),
arrowprops=dict(arrowstyle='->',
color=color,
connectionstyle='arc3,rad=0'))
import os
import sys
import numpy as np
import cv2
current_filepath = os.path.dirname(os.path.realpath(__file__))
sys.path.append(os.path.join(current_filepath, "../../utils"))
import python_utils
import polygon_utils
# --- Useful when code is executed inside Docker without a display: --- #
# Try importing pyplot:
display_is_available = python_utils.get_display_availability()
use_pyplot = None
if display_is_available:
if python_utils.module_exists("matplotlib.pyplot"):
# This means everything works with the default matplotlib backend
import matplotlib.pyplot as plt
use_pyplot = True
else:
# matplotlib.pyplot is just not available we cannot plot anything
use_pyplot = False
else:
# Try switching backend
import matplotlib
matplotlib.use('Agg')
if python_utils.module_exists("matplotlib.pyplot"):
# The Agg backend works, pyplot is available, we just can't display plots to the screen (they'll be saved to file anyway)
import matplotlib.pyplot as plt
use_pyplot = True
# --- --- #
import numpy as np
import time
import sklearn.datasets
import skimage.transform
import python_utils
import image_utils
# if python_utils.module_exists("matplotlib.pyplot"):
# import matplotlib.pyplot as plt
CV2 = False
if python_utils.module_exists("cv2"):
import cv2
CV2 = True
# import multiprocessing
#
# import python_utils
#
# if python_utils.module_exists("joblib"):
# from joblib import Parallel, delayed
# JOBLIB = True
# else:
# JOBLIB = False
# def plot_field_map(field_map):
# from mpl_toolkits.mplot3d import Axes3D
#
# row = np.linspace(0, 1, field_map.shape[0])
# col = np.linspace(0, 1, field_map.shape[1])
import math
import random
import numpy as np
import scipy.spatial
from PIL import Image, ImageDraw, ImageFilter
import skimage
import python_utils
if python_utils.module_exists("skimage.measure"):
from skimage.measure import approximate_polygon
if python_utils.module_exists("shapely"):
from shapely import geometry
def is_polygon_clockwise(polygon):
rolled_polygon = np.roll(polygon, shift=1, axis=0)
double_signed_area = np.sum((rolled_polygon[:, 0] - polygon[:, 0]) * (rolled_polygon[:, 1] + polygon[:, 1]))
if 0 < double_signed_area:
return True
else:
return False
def orient_polygon(polygon, orientation="CW"):
poly_is_orientated_cw = is_polygon_clockwise(polygon)
if (poly_is_orientated_cw and orientation == "CCW") or (not poly_is_orientated_cw and orientation == "CW"):
return np.flip(polygon, axis=0)
else:
import tensorflow as tf
import sys
import math
import numpy as np
sys.path.append("../../polygon")
import python_utils
import polygon_utils
if python_utils.module_exists("skimage.io"):
import skimage.io as io
# --- Params --- #
SEED = 0
RANDOM_CROP_AMPLITUDE = 0
# --- --- #
def polygon_flip_up_down(polygon, vertex_count, im_res):
invert_mat = np.array([[1, 0], [0, -1]], dtype=np.float16)
translate_mat = np.tile(np.array([0, im_res]), (vertex_count, 1))
polygon = tf.add(tf.matmul(polygon, invert_mat), translate_mat)
return polygon
def read_and_decode(tfrecords_filename,
im_res,