diff --git a/compute_features.py b/compute_features.py
index 958e47f89dca4ea4ebc04d910b9204f8bcd2dca0..92ba8f9a2bc70c1509799ed81c97019fbec56fe5 100644
--- a/compute_features.py
+++ b/compute_features.py
@@ -10,7 +10,7 @@ from pose import convert2
from matplotlib import image
from fps_alg import process2
import os
-
+from PIL import Image
def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, World_begin, Nb_world, list_categories, occ_target, vis):
transformation = np.matrix([[0.0000000, -1.0000000, 0.0000000],
@@ -88,7 +88,7 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
if categories in categories_occ_array.keys():
Nb_instance = len(categories_array[categories])
Nb_instance_occ = len(categories_occ_array[categories])
-
+
for scenario_loop in scenarios:
meta = {}
@@ -155,6 +155,21 @@ def process_compute(data_name, camera, camera_resized, new_size, Nb_camera, Worl
id = categories_occ_array[categories][0]
img = cv2.imread(f"{data_name}/Instance_Segmentation/{p}.png", cv2.IMREAD_UNCHANGED) # plt.imread(path)
+
+ depth = Image.open(f"{data_name}/Depth/{p}.tiff")
+ print(f"{data_name}/Depth/{p}.tiff")
+ for scenario_loop in scenarios:
+ if not destination_folders[scenario_loop] == "dont_save" :
+ depth_array = np.asarray(depth.getdata()).reshape(depth.size[1], depth.size[0])
+ depth1 = cv2.resize(np.array(depth), new_size)
+ depth2 = depth1 * 1000
+ depth3 = depth2.astype(np.uint32)
+ resized = Image.fromarray(depth3)
+ depth_high = Image.fromarray(depth_array)
+ #img2 = np.asarray(res.getdata()).reshape(res.size[1], res.size[0])
+ print(f"{data_name}/{destination_folders[scenario_loop]}/{categories}/Depth_resized/{p}.png")
+ #depth_high.save(f"{data_name}/{destination_folders[scenario_loop]}/{categories}/Depth_Gen/{p}.png")
+ resized.save(f"{data_name}/{destination_folders[scenario_loop]}/{categories}/Depth_resized/{p}.png")
instance_img = instance(img, id)
for scenario_loop in scenarios:
diff --git a/main.py b/main.py
index 8405c9c241a7f9c43bcce957654d0e6a3c6e221c..03a0b98e1b5ce080d59d97545c5d625def77c25c 100644
--- a/main.py
+++ b/main.py
@@ -8,16 +8,17 @@ import open3d as o3d
from scipy.spatial import distance
import argparse
+
def generate_folders(name, list_categories, scenario):
is_exist = os.path.exists(name)
if not is_exist:
os.mkdir(name)
- folders = ["RGB", "RGB_Gen", "RGB_resized", "Meta_Gen", "Depth", "Mask", "Meta", "Pose", "Bbox_2d", "Bbox_2d_loose", "Bbox_3d", "Bbox_3d_Gen", "Instance_Segmentation", "Semantic_Segmentation", "Instance_Mask", "Labels", "Instance_Mask_resized", "Occlusion", "Models", "Pose_transformed", "Bbox", "FPS", "FPS_resized"]
+ folders = ["RGB", "RGB_Gen", "RGB_resized", "Meta_Gen", "Depth", "Depth_Gen", "Depth_resized", "Mask", "Meta", "Pose", "Bbox_2d", "Bbox_2d_loose", "Bbox_3d", "Bbox_3d_Gen", "Instance_Segmentation", "Semantic_Segmentation", "Instance_Mask", "Labels", "Instance_Mask_resized", "Occlusion", "Models", "Pose_transformed", "Bbox", "FPS", "FPS_resized"]
for f in folders:
is_exist = os.path.exists(f"{name}/{f}")
if not is_exist:
- if f not in ["RGB_Gen", "RGB_resized", "Instance_Mask", "Labels", "Instance_Mask_resized", "Meta_Gen", "Models", "Pose_transformed", "Bbox", "Bbox_3d_Gen", "FPS" , "FPS_resized"]:
- os.mkdir(f"{name}/{f}")
+ if f not in ["RGB_Gen", "RGB_resized", "Depth", "Depth_Gen", "Depth_resized", "Instance_Mask", "Labels", "Instance_Mask_resized", "Meta_Gen", "Models", "Pose_transformed", "Bbox", "Bbox_3d_Gen", "FPS" , "FPS_resized"]:
+ os.mkdir(f"{name}/{f}") # general data not dependent of category
else:
for cat in list_categories:
is_exist2 = os.path.exists(f"{name}/Generated/{cat}")
@@ -60,8 +61,10 @@ if __name__ == '__main__':
parser.add_argument('--Nb_worlds', type=int, required=True)
parser.add_argument('--World_begin', type=int, required=True)
parser.add_argument('--dataset_id', type=str, required=True)
- parser.add_argument('--rearrange', type=bool, required=True)
- parser.add_argument('--compute', type=bool, required=True)
+ #parser.add_argument('--rearrange', dest='rearrange', default=False, action='store_true')
+ #parser.add_argument('--compute', dest='compute', default=False, action='store_true')
+ parser.add_argument('--rearrange', type=str, required=True)
+ parser.add_argument('--compute', type=str, required=True)
# Parse the argument
args = parser.parse_args()
@@ -110,8 +113,10 @@ if __name__ == '__main__':
new_camera = trans @ camera
#np.savetxt(f'{dataset_name}/Generated/camera_{choice}.txt', camera)
+ print("rearrange", args.rearrange)
+ print("compute", args.compute)
- if args.rearrange :
+ if args.rearrange == 'yes':
reform_data(dataset_src, dataset_name, dataset_type, Nb_camera, args.World_begin, args.Nb_worlds)
objs = {"banana1": [ 0.02949700132012367249, 0.1511049866676330566, 0.06059300713241100311 ],
@@ -142,6 +147,6 @@ if __name__ == '__main__':
bbox = get_3D_bbox(ext)
np.savetxt(f'{dataset_name}/Generated/{categories}/{categories}_bbox_3d.txt', bbox) # save
- if args.compute :
+ if args.compute == 'yes' :
process_compute(dataset_name, camera, new_camera, new_size, Nb_camera, args.World_begin, args.Nb_worlds, list_categories, occ_target, False)