import os
import numpy as np
import json
from prepare_data import reform_data
from pose import transform_pose
from bbox_2d import generate_2d_bbox
from instance_mask import generate_instance_mask
from fps_alg import generate_fps
from bbox_3d import generate_3d_bbox
import shutil
def compute_categories_id(data_name, world):
#Category = 'banana1'
#Category = 'pear2'
#Category = "orange2"
# Opening JSON file
f = open(f'{data_name}/Meta/{world}.json')
# returns JSON object as
# a dictionary
data = json.load(f)
# Iterating through the json
# list
catergories_label_to_id={}
catergories_id_to_label={}
catergories_instance_array_cat_to_id={}
catergories_instance_array_id_to_cat={}
for k in data['categories']:
catergories_label_to_id[k['label']]=k['id']
catergories_id_to_label[k['id']]=k['label']
catergories_instance_array_cat_to_id[k['label']]=[]
for k in data['objects']:
#print(k)
#catergories_instance_array[catergories_id_to_label[i['category_id']]]
catergories_instance_array_id_to_cat[k['id']] = catergories_id_to_label[k['category_id']]
catergories_instance_array_cat_to_id[catergories_id_to_label[k['category_id']]].append(k['id'])
# if i['category_id'] == id_category :
# print("Hello fruits instance")
# id_instances.append(i['id'])
# print(i['id'])
# print("catergories_instance_array_cat_to_id : ", catergories_instance_array_cat_to_id)
# print("catergories_instance_array_id_to_cat : ", catergories_instance_array_id_to_cat)
# Closing file
f.close()
return catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id
def generate_folders(name, list_categories):
is_exist = os.path.exists(name)
if not is_exist:
os.mkdir(name)
folders = ["RGB", "Depth", "Mask", "Meta", "Pose", "Bbox_2d", "Bbox_2d_loose", "Instance_Segmentation", "Semantic_Segmentation", "Instance_Mask", "Occlusion", "Models", "Pose_transformed", "Bbox", "FPS"]
for f in folders:
is_exist = os.path.exists(f"{name}/{f}")
if not is_exist:
if f not in ["RGB_Gen", "Instance_Mask", "Models", "Pose_transformed", "Bbox", "FPS"]:
os.mkdir(f"{name}/{f}")
else:
for cat in list_categories:
os.makedirs(f"{name}/Generated/{f}/{cat}")
# def compute_categories_id(dataset_src, world):
# #Category = 'banana1'
# #Category = 'pear2'
# #Category = "orange2"
# # Opening JSON file
# f = open(f'{dataset_src}/{world}/meta.json')
# # returns JSON object as
# # a dictionary
# data = json.load(f)
# # Iterating through the json
# # list
# id_category = 0
# catergories_label_to_id={}
# catergories_id_to_label={}
# catergories_instance_array_cat_to_id={}
# catergories_instance_array_id_to_cat={}
# for i in data['categories']:
# catergories_label_to_id[i['label']]=i['id']
# catergories_id_to_label[i['id']]=i['label']
# catergories_instance_array_cat_to_id[i['label']]=[]
# for i in data['objects']:
# print(i)
# #catergories_instance_array[catergories_id_to_label[i['category_id']]]
# catergories_instance_array_id_to_cat[i['id']] = catergories_id_to_label[i['category_id']]
# catergories_instance_array_cat_to_id[catergories_id_to_label[i['category_id']]].append(i['id'])
# # if i['category_id'] == id_category :
# # print("Hello fruits instance")
# # id_instances.append(i['id'])
# # print(i['id'])
# print("catergories_instance_array_cat_to_id : ", catergories_instance_array_cat_to_id)
# print("catergories_instance_array_id_to_cat : ", catergories_instance_array_id_to_cat)
# # Closing file
# f.close()
# return catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id
# def get_id_wanted(wanted_category):
# #Category = 'banana1'
# #Category = 'pear2'
# #Category = "orange2"
# # Opening JSON file
# f = open('/media/gduret/DATA/dataset/s2rg/Fruits_all_medium/data/1/meta.json')
# # returns JSON object as
# # a dictionary
# data = json.load(f)
# # Iterating through the json
# # list
# id_category = 0
# for i in data['categories']:
# print(i)
# if i['label'] == wanted_category :
# print("Hello fruits")
# id_category = i['id']
# print(id_category)
# id_instances = []
# for i in data['objects']:
# print(i)
# if i['category_id'] == id_category :
# print("Hello fruits instance")
# id_instances.append(i['id'])
# print(i['id'])
# print(id_instances)
# # Closing file
# f.close()
# return id_instances
# def compute_id_good_occ(dataset_src, world, camera, type_data, frame, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, Occ_wanted):
# f2 = open(f'{dataset_src}/{world}/grabber_{camera}/{type_data}/occlusion/{frame}.json')
# data2 = json.load(f2)
# catergories_occ_array = {}
# for cat in catergories_instance_array_cat_to_id :
# #print(cat)
# catergories_occ_array[cat] = []
# for i in data2:
# #print('i : ',i)
# #print(i['id'])
# #print(id_instances)
# if i['occlusion_value'] > 0.5 :
# catergories_occ_array[catergories_instance_array_id_to_cat[i['id']]].append(i['id'])
# # if i['id'] in id_instances :
# # print("Hello banana instance occ")
# # if i['occlusion_value'] > 0.5 :
# # id_instances_good.append(i['id'])
# # print(i['id'])
# # print(i['occlusion_value'])
# print(catergories_occ_array)
# # Closing file
# f2.close()
# return catergories_occ_array
# def get_id_good_occ(Occ_wanted):
# f2 = open('/media/gduret/DATA/dataset/s2rg/Fruits_all_medium/data/1/grabber_1/ground_truth_rgb/occlusion/4_158000000.json')
# data2 = json.load(f2)
# id_instances_good = []
# for i in data2:
# print('i : ',i)
# print(i['id'])
# print(id_instances)
# if i['id'] in id_instances :
# print("Hello banana instance occ")
# if i['occlusion_value'] > 0.5 :
# id_instances_good.append(i['id'])
# print(i['id'])
# print(i['occlusion_value'])
# print(id_instances_good)
# # Closing file
# f2.close()
if __name__ == '__main__':
#dataset_src = "/media/mahmoud/E/Fruits_easy/data"
# futur parameters :
Categories = [] # to read
Nb_instance = 1
occ_target = 0.5
#catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(dataset_name, 1)
dataset_src = "/media/gduret/DATA/dataset/s2rg/Fruits_all_medium/data"
choice = "low"
data_options = {"high": "ground_truth_rgb",
"low": "ground_truth_depth"}
dataset_type = data_options[choice]
#compute_id_good_occ(dataset_src, 1, 1, dataset_type, "1_926000000", catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, Occ_target)
dataset_name = f"GUIMOD_{choice}"
list_categories = ["banana1", "kiwi1", "pear2", "strawberry1", "apricot", "orange2", "peach1", "lemon2", "apple2" ]
generate_folders(dataset_name, list_categories)
for cat in list_categories:
src_bbox = f"Models/{cat}/{cat.lower()}.ply"
dst_bbox = f"{dataset_name}/Generated/Models/{cat}/{cat.lower()}.ply"
shutil.copy(src_bbox, dst_bbox)
if choice == 'high':
camera = np.matrix([[1386.4138492513919, 0.0, 960.5],
[0.0, 1386.4138492513919, 540.5],
[0.0, 0.0, 1.0]])
else:
camera = np.matrix([[1086.5054444841007, 0.0, 640.5],
[0.0, 1086.5054444841007, 360.5],
[0.0, 0.0, 1.0]])
np.savetxt(f'{dataset_name}/Generated/camera_{choice}.txt', camera)
# frame = "1_600000000"
frame = "1_926000000"
Nb_camera = 15
Nb_world = 2
reform_data(dataset_src, dataset_name, dataset_type, frame, Nb_camera, Nb_world)
transform_pose(dataset_name, Nb_camera, Nb_world, list_categories, occ_target)
generate_2d_bbox(dataset_name, Nb_camera, Nb_world, list_categories, occ_target)
generate_instance_mask(dataset_name, Nb_camera, Nb_world, list_categories, occ_target)
generate_fps(dataset_name, camera, Nb_camera, Nb_world, list_categories, True)
#generate_3d_bbox(dataset_name)