diff --git a/compute_features.py b/compute_features.py
index e7afe776ef8f11a831e0dd4e765adbf5181d431d..babf84be459ba8f06bbd26e6f90e0cdbb11fbeac 100644
--- a/compute_features.py
+++ b/compute_features.py
@@ -29,9 +29,6 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
for destination_folder_loop in destination_folders_list[scenario_loop] : # [f"Generated_{scenario}_Testing", f"Generated_{scenario}_Evaluating", f"Generated_{scenario}_Training"] :
list_count_categories[scenario_loop][destination_folder_loop] = {}
- print("destination_folders : ", destination_folders_list)
- print("list_count_categories : ", list_count_categories)
-
destination_folders = {}
for i in range(World_begin, World_begin + Nb_world): # worlds
@@ -70,8 +67,6 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
### 3D Poses ###
with open(f'{data_name}/Pose/{p}.json', 'r') as f:
data_3D_pose = json.load(f)
- #print(data)
- #print("len(data)", len(data_3D_pose))
### 2D BBox ###
with open(f"{data_name}/Bbox_2d/{p}.json", 'r') as f:
@@ -98,10 +93,8 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
meta = {}
#
if not destination_folders[scenario_loop] in list_count_categories[scenario_loop].keys():
- #list_count_categories[categories] = {categories}
list_count_categories[scenario_loop][destination_folders[scenario_loop]] = {}
if not categories in list_count_categories[scenario_loop][destination_folders[scenario_loop]].keys():
- #list_count_categories[categories] = {categories}
list_count_categories[scenario_loop][destination_folders[scenario_loop]][categories] = {}
if f"{Nb_instance}_instances" in list_count_categories[scenario_loop][destination_folders[scenario_loop]][categories].keys() :
list_count_categories[scenario_loop][destination_folders[scenario_loop]][categories][f"{Nb_instance}_instances"] += 1
@@ -142,7 +135,6 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
T_exp = transformation @ xyz
T_exp = np.array(T_exp)
num_arr = np.c_[R_exp, T_exp[0]]
- #for scenario_loop in scenarios:
np.save(f'{data_name}/Generated/{categories}/Pose_transformed/{p}.npy', num_arr) # save
else:
continue
@@ -222,19 +214,10 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
for scenario_loop in scenarios:
- print("scenarios : " , scenarios)
- print("scenario_loop : " , scenario_loop)
- print ("destination_folders : ", destination_folders )
for destination_folder_loop in destination_folders_list[scenario_loop] : # [f"Generated_{scenario}_Testing", f"Generated_{scenario}_Evaluating", f"Generated_{scenario}_Training"] :
- print("destination_folders[scenario_loop]", destination_folders_list[scenario_loop])
- print("destination_folder_loop", destination_folder_loop)
with open(f'{data_name}/{destination_folder_loop}/Count_{p}.json', mode='w') as f:
f.write(json.dumps(list_count_categories[scenario_loop][destination_folder_loop], indent=4))
- print(f'{data_name}/{destination_folders_list[scenario_loop]}/Count_{p}.json')
- print(list_count_categories[scenario_loop][destination_folder_loop])
-
-
with open(f'{data_name}/Count_{p}.json', mode='w') as f:
f.write(json.dumps(list_count_categories, indent=4))
- print(list_count_categories)
+ #print(list_count_categories)
diff --git a/fps_alg.py b/fps_alg.py
index fa2f93f64d93135cbf2cd3086aa82850a6401336..802a7ea4e01f5b052f20d7248443b470d300a4b8 100644
--- a/fps_alg.py
+++ b/fps_alg.py
@@ -132,8 +132,8 @@ def process(pcd_box, pcd2, R_exp, tVec, camera, img):
keypoint_2d = cv2.projectPoints(pcd2_in_numpy, R_exp, tVec, camera, np.zeros(shape=[5, 1], dtype='float64'))
keypoint_2d2 = cv2.projectPoints(pcd2_in_numpy2, R_exp, tVec, camera, np.zeros(shape=[5, 1], dtype='float64'))
- for n in range(len(pcd2_in_numpy)):
- print(pcd2_in_numpy[n], '==>', keypoint_2d[0][n])
+ # for n in range(len(pcd2_in_numpy)):
+ # print(pcd2_in_numpy[n], '==>', keypoint_2d[0][n])
points = []
for n in range(len(pcd2_in_numpy)):
@@ -203,5 +203,5 @@ def generate_fps(data_name, camera, Nb_camera, Nb_world, list_categories, occ_ta
out[0][ind + 1] = point[0][1] / img.shape[0]
ind += 2
np.savetxt(f'{data_name}/Generated/FPS/{categories}/{p}.txt', out)
- print("stop")
+
diff --git a/pose.py b/pose.py
index 6f8e477f506260722826c2b3d63b9c6fcc6379bc..6f29610c95e3042d8db920b78cb3b239ed3d200c 100644
--- a/pose.py
+++ b/pose.py
@@ -38,9 +38,6 @@ def compute_categories_id(data_name, world):
# 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()
@@ -63,8 +60,6 @@ def compute_id_good_occ(data_name, count, catergories_instance_array_id_to_cat,
if i['occlusion_value'] > 0.5 :
catergories_occ_array[catergories_instance_array_id_to_cat[i['id']]].append(i['id'])
- print(catergories_occ_array)
-
# Closing file
f2.close()
@@ -99,9 +94,6 @@ def transform_pose(data_name, Nb_camera, Nb_world, list_categories, occ_target):
with open(f'{data_name}/Pose/{p}.json', 'r') as f:
data = json.load(f)
- #print(data)
- print("len(data)", len(data))
-
for k in range(len(data)):
for categories in list_categories:
diff --git a/test_fps.py b/test_fps.py
index 9ed329ec5eb4d8f62ca35cd405e9be0283f43148..0a012a158e560f70568a4930443f957d0bcf1ac0 100644
--- a/test_fps.py
+++ b/test_fps.py
@@ -214,7 +214,7 @@ new = np.matrix([[0.0000000, -1.0000000, 0.0000000],
t_org = pose[0:3, 3]
tVec = new @ t_org
-print(tVec)
+#print(tVec)
img = image.imread('/media/mahmoud/F/GUIMOD/data/1/grabber_1/color/image/0_0.png')
camera = [[1386.4138492513919, 0.0, 960.5], [0.0, 1386.4138492513919, 540.5], [0.0, 0.0, 1.0]]
diff --git a/test_resize.py b/test_resize.py
index c014c5975f1ef22a590f3e70f8476481789afea2..84443b9312f564a0f3255e5d5debf643d5db0617 100644
--- a/test_resize.py
+++ b/test_resize.py
@@ -111,8 +111,8 @@ def process2(pcd, R_exp, tVec, camera, img, vis= True):
pcd_fps_numpy = np.asarray(pcd)
keypoint_2d = cv2.projectPoints(pcd_fps_numpy, R_exp, tVec, camera, np.zeros(shape=[8, 1], dtype='float64'))
- for n in range(len(pcd_fps_numpy)):
- print(pcd_fps_numpy[n], '==>', keypoint_2d[0][n])
+ # for n in range(len(pcd_fps_numpy)):
+ # print(pcd_fps_numpy[n], '==>', keypoint_2d[0][n])
if vis:
out = np.zeros((img.shape[0], img.shape[1], 16))
@@ -139,8 +139,8 @@ def process(pcd_box, pcd2, R_exp, tVec, camera, img):
keypoint_2d = cv2.projectPoints(pcd2_in_numpy, R_exp, tVec, camera, np.zeros(shape=[5, 1], dtype='float64'))
keypoint_2d2 = cv2.projectPoints(pcd2_in_numpy2, R_exp, tVec, camera, np.zeros(shape=[5, 1], dtype='float64'))
- for n in range(len(pcd2_in_numpy)):
- print(pcd2_in_numpy[n], '==>', keypoint_2d[0][n])
+ # for n in range(len(pcd2_in_numpy)):
+ # print(pcd2_in_numpy[n], '==>', keypoint_2d[0][n])
points = []
for n in range(len(pcd2_in_numpy)):
diff --git a/utils.py b/utils.py
index 2e09900181b6c4ba0515ce9fb69945c4b8af7759..b8f4b334e003e027307742ec8f7f69a73a306112 100644
--- a/utils.py
+++ b/utils.py
@@ -36,9 +36,6 @@ def compute_categories_id(data_name, world):
# 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()
@@ -57,15 +54,10 @@ def compute_id_good_occ(data_name, count, catergories_instance_array_id_to_cat,
#print(cat)
catergories_occ_array[cat] = []
- print(data2)
-
for i in data2:
if i['occlusion_value'] >= Occ_wanted :
- print(i['id'])
catergories_occ_array[catergories_instance_array_id_to_cat[i['id']]].append(i['id'])
- print(catergories_occ_array)
-
# Closing file
f2.close()