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import numpy as np
import json
import pdb
from matplotlib import pyplot as plt
import os
# from skimage.morphology import binary_dilation, binary_erosion
from scipy.ndimage import binary_dilation, binary_erosion, binary_hit_or_miss
import random
from ListSelEm import *
from Utils import Process, Change_Colour
def generate_inp_out_catB_Iteration(list_se_idx, k_iterate, **param):
"""
"""
base_img = np.zeros((param['img_size'], param['img_size']), dtype=np.int32)
sz = np.random.randint(3, 6)
idx1 = np.random.randint(0, param['img_size'], size=sz)
idx2 = np.random.randint(0, param['img_size'], size=sz)
base_img[idx1, idx2] = 1
for _ in range(2):
idx = np.random.randint(0, 8)
base_img = binary_dilation(base_img, list_se_3x3[idx])
inp_img = np.array(base_img, copy=True)
out_img = np.array(base_img, copy=True)
for idx in range(2):
out_img = binary_dilation(out_img, list_se_3x3[list_se_idx[idx]])
for idx in range(2):
out_img = binary_erosion(out_img, list_se_3x3[list_se_idx[idx]])
for idx in range(k_iterate):
out_img = binary_dilation(out_img, list_se_3x3[list_se_idx[-1]])
for idx in range(k_iterate):
out_img = binary_erosion(out_img, list_se_3x3[list_se_idx[-1]])
return inp_img, out_img
def generate_one_task_CatB_Iteration(**param):
"""
"""
number_subtasks = 3
list_se_idx = np.random.randint(0, 8, 3)
k_iterate = np.random.randint(2, 5)
data_tot = []
list_se_tot = []
k_subtask = 0
while k_subtask < number_subtasks:
data_subtask = []
k_example = 0
list_se_subtask = np.array(list_se_idx, copy=True)
for idx in [0, 1]:
idx_tmp = np.random.randint(0, 8)
list_se_subtask[idx] = idx_tmp
while k_example < param['no_examples_per_task']:
inp_img, out_img = generate_inp_out_catB_Iteration(list_se_subtask, k_iterate, **param)
# Check if both input and output images are non-trivial
FLAG = False
if np.all(inp_img*1 == 1) or np.all(inp_img*1 == 0):
FLAG = True
elif np.all(out_img*1 == 1) or np.all(out_img*1 == 0):
FLAG = True
if FLAG:
# If trivial regenerate the list of se's
# And reset all variables!!
data_subtask = []
k_example = -1
list_se_subtask = np.array(list_se_idx, copy=True)
for idx in [0, 1]:
idx_tmp = np.random.randint(0, 8)
list_se_subtask[idx] = idx_tmp
else:
# If not trivial proceed.
data_subtask.append((inp_img, out_img, k_subtask))
k_example += 1
data_tot += data_subtask
list_se_tot.append(list_se_subtask)
k_subtask += 1
return data_tot, list_se_tot, k_iterate
def write_dict_json_CatB_Iteration(data, fname):
"""
"""
dict_data = []
for (inp, out, subtask) in data:
inp = [[int(y) for y in x] for x in inp]
out = [[int(y) for y in x] for x in out]
dict_data.append({"input": inp, "output": out, "subtask": subtask})
with open(fname, "w") as f:
f.write(json.dumps(dict_data))
def write_solution_CatB_Iteration(list_se_idx, k_iterate, fname):
"""
"""
with open(fname, 'w') as f:
for list_se_idx_subtask in list_se_idx:
f.write("Subtask \n")
f.write("-------- \n")
i = 0
while i < 2:
f.write("Dilation SE{}\n".format(list_se_idx_subtask[i]+1))
i += 1
i = 0
while i < 2:
f.write(" Erosion SE{}\n".format(list_se_idx_subtask[i]+1))
i += 1
i = 2
f.write("Iterate {} Dilation SE{}\n".format(k_iterate, list_se_idx_subtask[i]+1))
f.write("Iterate {} Erosion SE{}\n".format(k_iterate, list_se_idx_subtask[i]+1))
f.write("\n")
def write_solution_CatB_Iteration_json(list_se_idx, k_iterate, fname):
"""
Solution written in format:
subtask -
n_iterate -
op - Dilation/Erosion/Color_Change
SE = SE0-SE7
"""
data = []
subtask = 0
for list_se_idx_subtask in list_se_idx:
i = 0
while i < 2:
data.append((subtask, 1, 'Dilation', 'SE{}'.format(list_se_idx_subtask[i]+1)))
i += 1
i = 0
while i < 2:
data.append((subtask, 1, 'Erosion', 'SE{}'.format(list_se_idx_subtask[i]+1)))
i += 1
data.append((subtask, k_iterate, 'Dilation', 'SE{}'.format(list_se_idx_subtask[i]+1)))
data.append((subtask, k_iterate, 'Erosion', 'SE{}'.format(list_se_idx_subtask[i]+1)))
subtask += 1
with open(fname, "w") as f:
f.write(json.dumps(data))
def generate_100_tasks_CatB_Iteration(seed, **param):
"""
"""
np.random.seed(seed)
os.makedirs("./Dataset/CatB_Iteration", exist_ok=True)
for task_no in range(100):
data, list_se_idx, k_iterate = generate_one_task_CatB_Iteration(**param)
fname = './Dataset/CatB_Iteration/Task{:03d}.json'.format(task_no)
write_dict_json_CatB_Iteration(data, fname)
fname = './Dataset/CatB_Iteration/Task{:03d}_soln.txt'.format(task_no)
write_solution_CatB_Iteration(list_se_idx, k_iterate, fname)
fname = './Dataset/CatB_Iteration/Task{:03d}_soln.json'.format(task_no)
write_solution_CatB_Iteration_json(list_se_idx, k_iterate, fname)
if __name__ == "__main__":
param = {}
param['img_size'] = 15
param['se_size'] = 5 # Size of the structuring element
param['seq_length'] = 4 # Number of primitives would be 2*param['seq_length']
param['no_examples_per_task'] = 4
param['no_colors'] = 3
generate_100_tasks_CatB_Iteration(32, **param)
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