diff --git a/compute_label.py b/compute_label.py
index 559f303b9a93cad0994b1bb815793e64a86eb2c9..60039e39300e52902a068c0ef0291d5c695e53fc 100644
--- a/compute_label.py
+++ b/compute_label.py
@@ -2,6 +2,7 @@ import numpy as np
import yaml
import os
import argparse
+import shutil
if __name__ == "__main__":
@@ -10,10 +11,12 @@ if __name__ == "__main__":
# Add an argument
parser.add_argument('--path_dataset', type=str, required=True)
parser.add_argument('--target_folder', type=str, required=True)
+ parser.add_argument('--path_DF_data', type=str, required=True)
# Parse the argument
args = parser.parse_args()
target_folder = args.target_folder
+ path_data_df = args.path_DF_data
#objects = ["apple2", "banana1", "pear2"]
objects = ["apple2", "apricot", "banana1", "kiwi1", "lemon2", "orange2", "peach1", "pear2"]
@@ -25,54 +28,113 @@ if __name__ == "__main__":
#path_data = "GUIMOD_low/Pose_transformed"
#path_data = "/gpfsscratch/rech/uli/ubn15wo/dataset1/s2rg/Fruits_all_medium/GUIMOD_low/Generated_Worlds_Training/orange2/Pose_transformed/"
#path_data = f"/gpfsscratch/rech/uli/ubn15wo/dataset1/s2rg/Fruits_all_medium/GUIMOD_low/{target_folder}/"
- path_data = f"{args.path_dataset}/{target_folder}"
+
+ for split in ["_Training","_Evaluating"]:
+ path_data = f"{args.path_dataset}/{target_folder}{split}"
+
+ if not os.path.exists(path_data_df) :
+ os.makedirs(path_data_df)
+
+
+ for obj in objects:
+ print(f"move {path_data} to {path_data_df}")
+
+ if not os.path.exists(f"{path_data_df}/0{obj_ids[obj]}") :
+ os.makedirs(f"{path_data_df}/0{obj_ids[obj]}")
+ if not os.path.exists(f"{path_data_df}/0{obj_ids[obj]}/depth/") :
+ os.makedirs(f"{path_data_df}/0{obj_ids[obj]}/depth/")
+ if not os.path.exists(f"{path_data_df}/0{obj_ids[obj]}/rgb/") :
+ os.makedirs(f"{path_data_df}/0{obj_ids[obj]}/rgb/")
+ if not os.path.exists(f"{path_data_df}/0{obj_ids[obj]}/mask/") :
+ os.makedirs(f"{path_data_df}/0{obj_ids[obj]}/mask/")
+
+ os.system(f"cp -r {path_data}/{obj}/Depth_resized/* {path_data_df}/0{obj_ids[obj]}/depth/")
+ os.system(f"cp -r {path_data}/{obj}/RGB_resized/* {path_data_df}/0{obj_ids[obj]}/rgb/")
+ os.system(f"cp -r {path_data}/{obj}/Instance_Mask_resized/* {path_data_df}/0{obj_ids[obj]}/mask/")
+
+ #shutil.copytree(f"{path_data}/{obj}/Depth_resized", f"{path_data_df}/0{obj_ids[obj]}/depth", dirs_exist_ok = True,)
+ #shutil.copytree(f"{path_data}/{obj}/RGB_resized", f"{path_data_df}/0{obj_ids[obj]}/rgb", dirs_exist_ok = True)
+ #shutil.copytree(f"{path_data}/{obj}/Instance_Mask_resized", f"{path_data_df}/0{obj_ids[obj]}/mask", dirs_exist_ok = True)
+
+ for obj in objects:
+ file = path_data + "/" + obj
+ #path_gt_obj = f"{obj_ids[obj]}/gt_new.yml"
+ path_gt_obj = f"{path_data_df}/0{obj_ids[obj]}/gt_{target_folder}{split}.yml"
+ #path_bbox = "GUIMOD_low/Bbox/" + obj
+ path_bbox = f"{path_data}/{obj}/Bbox/"
+
+ object_dicts = {}
+ print(file)
+ path_poses = file + "/Pose_transformed"
+ print("poses ", path_poses)
+ print("list : ", os.listdir(path_poses))
+ list_poses = os.listdir(path_poses)
+
+ print("-------------------------------------------------------------------------------------------------------")
+ print("-------------------------------------------------------------------------------------------------------")
+
+ if split=="_Training" :
+ with open(f"{path_data_df}/0{obj_ids[obj]}/train.txt", 'w') as f:
+ for filename2 in os.listdir(path_poses):
+ id_file2=filename2.split('.')[0]
+ print(id_file2+".png")
+ f.write(f'{id_file2}.png')
+ f.write('\n')
+
+ elif split=="_Evaluating" :
+ with open(f"{path_data_df}/0{obj_ids[obj]}/test.txt", 'w') as f:
+ for filename2 in os.listdir(path_poses):
+ id_file2=filename2.split('.')[0]
+ print(id_file2+".png")
+ f.write(f'{id_file2}.png')
+ f.write('\n')
+ else :
+ raise("not in traing or evaluating")
+
+ with open(path_gt_obj, 'w') as yaml_file:
+ for filename in os.listdir(path_poses):
+ #for i in range(num_rgb):
+ data_file = path_poses + "/" + filename
+ #print("filename : ", filename)
+ #data_file = file + "/" + str(i) + ".npy"
+ #print(list_RGB[4].split('.')[0])
+ id_file=filename.split('.')[0]
+ #print(id_file)
+ #print(filename)
+ #final_path_bbox = path_bbox + "/" + str(i) + ".txt"
+ final_path_bbox = path_bbox + "/" + id_file + ".txt"
+ #print(final_path_bbox)
+ bbox_file = open(final_path_bbox, "r")
+ line = bbox_file.readline()
+ bbox_string = line.split(" ")
+ bbox = [float(val) for val in bbox_string]
+ bbox2 = [int(bbox[0] * 0.5), int(bbox[1] * (2 / 3)), int(bbox[2] * 0.5), int(bbox[3] * (2 / 3))]
+ # print(bbox2)
+ bbox_file.close()
+
+ data = np.load(data_file)
+ cam_R_m2c = np.concatenate((data[0, 0:3], data[1, 0:3], data[2, 0:3]), axis=0).tolist()
+ cam_t_m2c = np.array((float(data[0, 3])*1000.0, float(data[1, 3])*1000.0, float(data[2, 3]*1000.0))).tolist()
+ object_dicts[id_file] = [{"cam_R_m2c": cam_R_m2c, "cam_t_m2c": cam_t_m2c, "obj_bb": bbox2, "obj_id": obj_ids[obj]}]
+ yaml.dump(object_dicts, yaml_file, default_flow_style=None)
+
+
for obj in objects:
- file = path_data + "/" + obj
- #path_gt_obj = f"{obj_ids[obj]}/gt_new.yml"
- path_gt_obj = f"/gpfsscratch/rech/uli/ubn15wo/DenseFusion/datasets/linemod/Linemod_preprocessed/data/0{obj_ids[obj]}/gt_{target_folder}.yml"
- #path_bbox = "GUIMOD_low/Bbox/" + obj
- path_bbox = f"{path_data}/{obj}/Bbox/"
-
- object_dicts = {}
- print(file)
- path_poses = file + "/Pose_transformed"
- print("poses ", path_poses)
- print("list : ", os.listdir(path_poses))
- list_poses = os.listdir(path_poses)
-
- print("-------------------------------------------------------------------------------------------------------")
- print("-------------------------------------------------------------------------------------------------------")
- with open(f"/gpfsscratch/rech/uli/ubn15wo/DenseFusion/datasets/linemod/Linemod_preprocessed/data/0{obj_ids[obj]}/split_file_{target_folder}.txt", 'w') as f:
- for filename2 in os.listdir(path_poses):
- id_file2=filename2.split('.')[0]
- print(id_file2+".png")
- f.write(f'{id_file2}.png')
- f.write('\n')
-
- with open(path_gt_obj, 'w') as yaml_file:
- for filename in os.listdir(path_poses):
- #for i in range(num_rgb):
- data_file = path_poses + "/" + filename
- print("filename : ", filename)
- #data_file = file + "/" + str(i) + ".npy"
- #print(list_RGB[4].split('.')[0])
- id_file=filename.split('.')[0]
- print(id_file)
- print(filename)
- #final_path_bbox = path_bbox + "/" + str(i) + ".txt"
- final_path_bbox = path_bbox + "/" + id_file + ".txt"
- print(final_path_bbox)
- bbox_file = open(final_path_bbox, "r")
- line = bbox_file.readline()
- bbox_string = line.split(" ")
- bbox = [float(val) for val in bbox_string]
- bbox2 = [int(bbox[0] * 0.5), int(bbox[1] * (2 / 3)), int(bbox[2] * 0.5), int(bbox[3] * (2 / 3))]
- # print(bbox2)
- bbox_file.close()
-
- data = np.load(data_file)
- cam_R_m2c = np.concatenate((data[0, 0:3], data[1, 0:3], data[2, 0:3]), axis=0).tolist()
- cam_t_m2c = np.array((float(data[0, 3])*1000.0, float(data[1, 3])*1000.0, float(data[2, 3]*1000.0))).tolist()
- object_dicts[id_file] = [{"cam_R_m2c": cam_R_m2c, "cam_t_m2c": cam_t_m2c, "obj_bb": bbox2, "obj_id": obj_ids[obj]}]
- yaml.dump(object_dicts, yaml_file, default_flow_style=None)
+
+ # Reading data from file1
+ with open(f"{path_data_df}/0{obj_ids[obj]}/gt_{target_folder}_Training.yml") as fp:
+ data_train = fp.read()
+
+ # Reading data from file2
+ with open(f"{path_data_df}/0{obj_ids[obj]}/gt_{target_folder}_Evaluating.yml") as fp:
+ data_eval = fp.read()
+
+ # Merging 2 files
+ # To add the data of file2
+ # from next line
+ data_gt = data_train
+ data_gt += data_eval
+
+ with open (f"{path_data_df}/0{obj_ids[obj]}/gt.yml", 'w') as fp:
+ fp.write(data_gt)
\ No newline at end of file