diff --git a/bbox_2d.py b/bbox_2d.py
index c8513ae7ee994af979c4282d559ffb1eb52c69ef..451286288c8844f0b8aa533bd86034f21d1a4d2c 100644
--- a/bbox_2d.py
+++ b/bbox_2d.py
@@ -3,6 +3,95 @@ import numpy as np
import json
+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 compute_id_good_occ(data_name, count, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, Occ_wanted):
+
+ f2 = open(f'{data_name}/Occlusion/{count}.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 bbox_2d(data_sample):
center = data_sample['bbox']['center']
@@ -19,31 +108,34 @@ def bbox_2d(data_sample):
return bbox_res
-def generate_2d_bbox(data_name, Nb_camera, Nb_world):
+def generate_2d_bbox(data_name, Nb_camera, Nb_world, list_categories, occ_target):
cont1, cont2, cont3 = 0, 0, 0
num_arr = 0
- for p in range(1, Nb_camera*Nb_world +1 ):
- with open(f"{data_name}/Bbox_2d/{p}.json", 'r') as f:
- data = json.load(f)
-
- for i in range(len(data)):
- if data[i]['id'] == 4:
- cont1 += 1
- bbox = bbox_2d(data[i])
- np.savetxt(f'{data_name}/Generated/Bbox/banana1/{p}.txt', np.array(bbox).reshape((1, 4))) # save
-
- elif data[i]['id'] == 5:
- cont2 += 1
- bbox = bbox_2d(data[i])
- np.savetxt(f'{data_name}/Generated/Bbox/orange2/{p}.txt', np.array(bbox).reshape((1, 4))) # save
-
- elif data[i]['id'] == 6:
- cont3 += 1
- bbox = bbox_2d(data[i])
- np.savetxt(f'{data_name}/Generated/Bbox/pear2/{p}.txt', np.array(bbox).reshape((1, 4))) # save
-
- else:
- continue
+
+
+ for i in range(1, Nb_world + 1): # worlds
+
+ catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(data_name, i)
+
+ for j in range(1, Nb_camera+1): # cameras
+ p = ((i-1)*Nb_camera) + j
+
+ catergories_occ_array = compute_id_good_occ(data_name, p, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, occ_target)
+
+ with open(f"{data_name}/Bbox_2d/{p}.json", 'r') as f:
+ data = json.load(f)
+
+ for k in range(len(data)):
+
+ for categories in list_categories:
+
+ if len(catergories_occ_array[categories]) == 1 and data[k]['id'] == catergories_occ_array[categories][0]:
+
+ cont1 += 1
+ bbox = bbox_2d(data[k])
+ np.savetxt(f'{data_name}/Generated/Bbox/{categories}/{p}.txt', np.array(bbox).reshape((1, 4))) # save
+ else:
+ continue
print(cont1, cont2, cont3)
diff --git a/fps_alg.py b/fps_alg.py
index 6ab1870191ebaf7a61a1355ef614309ed94092f3..a1f035f5468e029c48882960fd2935b8989de4cd 100644
--- a/fps_alg.py
+++ b/fps_alg.py
@@ -106,8 +106,13 @@ def process2(pcd, R_exp, tVec, camera, img, vis= True):
# pcd_fps.points = o3d.utility.Vector3dVector(pcd)
camera = np.array(camera)
+ print(R_exp)
R_exp = np.array(R_exp, dtype="float64")
+ print(R_exp)
+ print(tVec)
tVec = np.array(tVec, dtype="float64")
+ print(tVec)
+
pcd_fps_numpy = np.asarray(pcd)
keypoint_2d = cv2.projectPoints(pcd_fps_numpy, R_exp, tVec, camera, np.zeros(shape=[5, 1], dtype='float64'))
@@ -132,7 +137,10 @@ def process(pcd_box, pcd2, R_exp, tVec, camera, img):
camera = np.array(camera)
R_exp = np.array(R_exp, dtype="float64")
+ print(R_exp)
tVec = np.array(tVec, dtype="float64")
+ print(tVec)
+
pcd2_in_numpy2 = np.asarray(pcd2.points)
pcd2_in_numpy = pcd_box
@@ -181,10 +189,16 @@ def generate_fps(data_name, camera, Nb_camera, Nb_world, list_objects, vis=False
if path.is_file():
img = image.imread(f"{data_name}/RGB/{i}.png")
+
+ np.set_printoptions(precision=15)
pose = np.load(f'{data_name}/Generated/Pose_transformed/{obj}/{i}.npy')
+ print(pose)
R_exp = pose[0:3, 0:3]
tVec = pose[0:3, 3]
+ print(tVec)
+
+
# camera = np.matrix([[1386.4138492513919, 0.0, 960.5],
# [0.0, 1386.4138492513919, 540.5],
# [0.0, 0.0, 1.0]])
diff --git a/instance_mask.py b/instance_mask.py
index 6e7b7e2056c9d76c1b582eb20f931a6c0550d380..5ad4d4eb81cab7ce958f4c790a9fa9f6e96f36ea 100644
--- a/instance_mask.py
+++ b/instance_mask.py
@@ -104,33 +104,39 @@ def instance(im, id):
return im
-def generate_instance_mask(data_name, Nb_camera, Nb_world):
- ids = {"banana1": 25, "orange2": 36, "pear2": 121}
+def generate_instance_mask(data_name, Nb_camera, Nb_world,list_categories, occ_target):
+
for i in range(1, Nb_world + 1): # worlds
- #catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(data_name, i)
+ catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(data_name, i)
for j in range(1, Nb_camera+1): # cameras
k = ((i-1)*Nb_camera) + j
- #catergories_occ_array = compute_id_good_occ(data_name, p, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, occ_target)
-
- for key in ids.keys():
- id = ids[key]
- path = Path(f"{data_name}/Instance_Segmentation/{k}.png")
- if path.is_file():
- print("iddd : ",id)
- img = cv2.imread(f"{data_name}/Instance_Segmentation/{k}.png", cv2.IMREAD_UNCHANGED) # plt.imread(path)
+ catergories_occ_array = compute_id_good_occ(data_name, k, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, occ_target)
+
+
+ for categories in list_categories:
+
+ if len(catergories_occ_array[categories]) == 1 :
+
+
+ path = Path(f"{data_name}/Instance_Segmentation/{k}.png")
+ if path.is_file():
+ id = catergories_occ_array[categories][0]
+ print("iddd : ",id)
+ img = cv2.imread(f"{data_name}/Instance_Segmentation/{k}.png", cv2.IMREAD_UNCHANGED) # plt.imread(path)
+
+ #print("img[817][308] : ", img[817][308])
+ print("img[308][817] : ", img[308][817])
- #print("img[817][308] : ", img[817][308])
- print("img[308][817] : ", img[308][817])
+ instance_img = instance(img, id)
+ print("instance_img[308][817] : ", instance_img[308][817])
- instance_img = instance(img, id)
- print("instance_img[308][817] : ", instance_img[308][817])
+ cv2.imwrite(f"{data_name}/Generated/Instance_Mask/{categories}/{k}.png", 255*instance_img)
- cv2.imwrite(f"{data_name}/Generated/Instance_Mask/{key}/{k}.png", 255*instance_img)
diff --git a/main.py b/main.py
index f62320abd6b79515c64d11865f0248d23c74d679..e5d7d92dd5e63166e8e162d47049ec831ccc4bc6 100644
--- a/main.py
+++ b/main.py
@@ -10,30 +10,14 @@ from bbox_3d import generate_3d_bbox
import shutil
-def generate_folders(name):
- 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:
- os.makedirs(f"{name}/Generated/{f}/banana1")
- os.makedirs(f"{name}/Generated/{f}/orange2")
- os.makedirs(f"{name}/Generated/{f}/pear2")
-
-def compute_categories_id(dataset_src, world):
+def compute_categories_id(data_name, world):
#Category = 'banana1'
#Category = 'pear2'
#Category = "orange2"
# Opening JSON file
- f = open(f'{dataset_src}/{world}/meta.json')
+ f = open(f'{data_name}/Meta/{world}.json')
# returns JSON object as
# a dictionary
@@ -42,29 +26,28 @@ def compute_categories_id(dataset_src, world):
# 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 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 i in data['objects']:
- print(i)
+ for k in data['objects']:
+ #print(k)
#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'])
+ 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)
+ # 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
@@ -73,115 +56,178 @@ def compute_categories_id(dataset_src, world):
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 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')
+
+
+# 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)
+# # returns JSON object as
+# # a dictionary
+# data = json.load(f)
- # Iterating through the json
- # list
+# # Iterating through the json
+# # list
- id_category = 0
+# 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']:
- print(i)
- if i['label'] == wanted_category :
- print("Hello fruits")
- id_category = i['id']
- print(id_category)
+# 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']]=[]
- id_instances = []
+# 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'])
- 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("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)
- print(id_instances)
- # Closing file
- f.close()
+# # Closing file
+# f.close()
- return id_instances
+# return catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id
-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')
+# 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
- data2 = json.load(f2)
+# 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)
- catergories_occ_array = {}
+# id_instances = []
- for cat in catergories_instance_array_cat_to_id :
- #print(cat)
+# 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'])
- catergories_occ_array[cat] = []
+# print(id_instances)
- 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'])
+# # Closing file
+# f.close()
+# return 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'])
+# 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):
- print(catergories_occ_array)
+# f2 = open(f'{dataset_src}/{world}/grabber_{camera}/{type_data}/occlusion/{frame}.json')
+# data2 = json.load(f2)
+# catergories_occ_array = {}
- # Closing file
- f2.close()
+# for cat in catergories_instance_array_cat_to_id :
+# #print(cat)
- return catergories_occ_array
+# 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'])
-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)
+# # 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'])
- id_instances_good = []
+# print(catergories_occ_array)
- 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()
+# return catergories_occ_array
- # Closing file
- f2.close()
+# 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__':
@@ -191,16 +237,13 @@ if __name__ == '__main__':
Categories = [] # to read
Nb_instance = 1
- Occ_target = 0.5
+ occ_target = 0.5
+ #catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(dataset_name, 1)
- #Category = 'banana1'
- Category = 'pear2'
- #Category = "orange2"
dataset_src = "/media/gduret/DATA/dataset/s2rg/Fruits_all_medium/data"
- catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id = compute_categories_id(dataset_src, 1)
choice = "low"
data_options = {"high": "ground_truth_rgb",
@@ -208,15 +251,17 @@ if __name__ == '__main__':
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)
+ #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}"
- generate_folders(dataset_name)
- list_obj = ["banana1", "orange2", "pear2"]
- for obj in list_obj:
- src_bbox = f"Models/{obj}/{obj.lower()}.ply"
- dst_bbox = f"{dataset_name}/Generated/Models/{obj}/{obj.lower()}.ply"
+ 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':
@@ -236,8 +281,8 @@ if __name__ == '__main__':
Nb_world = 2
reform_data(dataset_src, dataset_name, dataset_type, frame, Nb_camera, Nb_world)
- transform_pose(dataset_name, Nb_camera, Nb_world, Occ_target)
- generate_2d_bbox(dataset_name, Nb_camera, Nb_world)
- generate_instance_mask(dataset_name, Nb_camera, Nb_world)
- generate_fps(dataset_name, camera, Nb_camera, Nb_world, list_obj, False)
+ 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)
diff --git a/pose.py b/pose.py
index 4f0293e529d1908cab06e52ddeaebf406abc7b09..6f8e477f506260722826c2b3d63b9c6fcc6379bc 100644
--- a/pose.py
+++ b/pose.py
@@ -80,7 +80,7 @@ def convert2(xyz):
return rotation
-def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
+def transform_pose(data_name, Nb_camera, Nb_world, list_categories, occ_target):
transformation = np.matrix([[0.0000000, -1.0000000, 0.0000000],
[0.0000000, 0.0000000, -1.0000000],
[1.0000000, 0.0000000, 0.0000000]])
@@ -94,6 +94,9 @@ def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
catergories_occ_array = compute_id_good_occ(data_name, p, catergories_instance_array_id_to_cat, catergories_instance_array_cat_to_id, occ_target)
+
+ ### Generate Poses ###
+
with open(f'{data_name}/Pose/{p}.json', 'r') as f:
data = json.load(f)
#print(data)
@@ -101,46 +104,22 @@ def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
for k in range(len(data)):
-
- if len(catergories_occ_array['banana1']) == 1 and data[k]['id'] == catergories_occ_array['banana1'][0]:
- cont1 += 1
- rpy = data[k]['pose']['rpy']
- rot = convert2(rpy)
- R_exp = transformation @ rot
- R_exp = np.array(R_exp)
-
- xyz = data[k]['pose']['xyz']
- T_exp = transformation @ xyz
- T_exp = np.array(T_exp)
- num_arr = np.c_[R_exp, T_exp[0]]
- np.save(f'{data_name}/Generated/Pose_transformed/banana1/{p}.npy', num_arr) # save
-
- elif len(catergories_occ_array['orange2']) == 1 and data[k]['id'] == catergories_occ_array['orange2'][0]:
- cont2 += 1
- rpy = data[k]['pose']['rpy']
- rot = convert2(rpy)
- R_exp = transformation @ rot
- R_exp = np.array(R_exp)
-
- xyz = data[k]['pose']['xyz']
- T_exp = transformation @ xyz
- T_exp = np.array(T_exp)
- num_arr = np.c_[R_exp, T_exp[0]]
- np.save(f'{data_name}/Generated/Pose_transformed/orange2/{p}.npy', num_arr) # save
-
- elif len(catergories_occ_array['pear2']) == 1 and data[k]['id'] == catergories_occ_array['pear2'][0]:
- cont3 += 1
- rpy = data[k]['pose']['rpy']
- rot = convert2(rpy)
- R_exp = transformation @ rot
- R_exp = np.array(R_exp)
-
- xyz = data[k]['pose']['xyz']
- T_exp = transformation @ xyz
- T_exp = np.array(T_exp)
- num_arr = np.c_[R_exp, T_exp[0]]
- np.save(f'{data_name}/Generated/Pose_transformed/pear2/{p}.npy', num_arr) # save
- else:
- continue
+ for categories in list_categories:
+
+ if len(catergories_occ_array[categories]) == 1 and data[k]['id'] == catergories_occ_array[categories][0]:
+ cont1 += 1
+ rpy = data[k]['pose']['rpy']
+ rot = convert2(rpy)
+ R_exp = transformation @ rot
+ R_exp = np.array(R_exp)
+
+ xyz = data[k]['pose']['xyz']
+ T_exp = transformation @ xyz
+ T_exp = np.array(T_exp)
+ num_arr = np.c_[R_exp, T_exp[0]]
+ np.save(f'{data_name}/Generated/Pose_transformed/{categories}/{p}.npy', num_arr) # save
+ else:
+ continue
+
print(cont1, cont2, cont3)