isolate generated data for learning from raw data

bbox_2d.py

@@ -31,17 +31,17 @@ def generate_2d_bbox(data_name, Nb_camera, Nb_world):
             if data[i]['id'] == 4:
                 cont1 += 1
                 bbox = bbox_2d(data[i])
-                np.savetxt(f'{data_name}/Bbox/banana1/{p}.txt', np.array(bbox).reshape((1, 4)))  # save
+                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}/Bbox/orange2/{p}.txt', np.array(bbox).reshape((1, 4)))  # save
+                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}/Bbox/pear2/{p}.txt', np.array(bbox).reshape((1, 4)))  # save
+                np.savetxt(f'{data_name}/Generated/Bbox/pear2/{p}.txt', np.array(bbox).reshape((1, 4)))  # save
 
             else:
                 continue

bbox_3d.py

@@ -23,6 +23,6 @@ def generate_3d_bbox(data_name):
     for key, val in objs.items():
         ext = [x / 2 for x in val]
         bbox = get_bbox(ext)
-        np.savetxt(f'{data_name}/Bbox/{key}_bbox_3d.txt', bbox)
+        np.savetxt(f'{data_name}/Generated/Bbox/{key}_bbox_3d.txt', bbox)
         # print(ext)
 

fps_alg.py

@@ -167,21 +167,21 @@ def generate_fps(data_name, camera, Nb_camera, Nb_world, list_objects, vis=False
     # Read the point cloud
     for obj in list_objects:
         obj_id = 1
-        point_cloud = f'{data_name}/Models/{obj}/{obj.lower()}.ply'
+        point_cloud = f'{data_name}/Generated/Models/{obj}/{obj.lower()}.ply'
         pcd = o3d.io.read_point_cloud(point_cloud)
 
         print("pcd", pcd)
 
 
         fps_points = apply_fps(pcd, 200)
-        np.savetxt(f'{data_name}/FPS/{obj}_fps_3d.txt', fps_points)
+        np.savetxt(f'{data_name}/Generated/FPS/{obj}_fps_3d.txt', fps_points)
 
         for i in range(1, Nb_camera*Nb_world +1):
-            path = Path(f'{data_name}/Pose_transformed/{obj}/{i}.npy') 
+            path = Path(f'{data_name}/Generated/Pose_transformed/{obj}/{i}.npy') 
             if path.is_file():
                 img = image.imread(f"{data_name}/RGB/{i}.png")
 
-                pose = np.load(f'{data_name}/Pose_transformed/{obj}/{i}.npy')
+                pose = np.load(f'{data_name}/Generated/Pose_transformed/{obj}/{i}.npy')
                 R_exp = pose[0:3, 0:3]
                 tVec = pose[0:3, 3]
 
@@ -199,6 +199,6 @@ def generate_fps(data_name, camera, Nb_camera, Nb_world, list_objects, vis=False
                     out[0][ind] = point[0][0] / img.shape[1]
                     out[0][ind + 1] = point[0][1] / img.shape[0]
                     ind += 2
-                np.savetxt(f'{data_name}/FPS/{obj}/{i}.txt', out)
+                np.savetxt(f'{data_name}/Generated/FPS/{obj}/{i}.txt', out)
                 print("stop")
     obj_id += 1

instance_mask.py

@@ -131,5 +131,6 @@ def generate_instance_mask(data_name, Nb_camera, Nb_world):
                     instance_img = instance(img, id)
                     print("instance_img[308][817] : ", instance_img[308][817])
 
-                    cv2.imwrite(f"{data_name}/Instance_Mask/{key}/{k}.png", 255*instance_img)
+
+                    cv2.imwrite(f"{data_name}/Generated/Instance_Mask/{key}/{k}.png", 255*instance_img)
 

main.py

@@ -19,12 +19,12 @@ def generate_folders(name):
     for f in folders:
         is_exist = os.path.exists(f"{name}/{f}")
         if not is_exist:
-            if f not in ["Instance_Mask", "Models", "Pose_transformed", "Bbox", "FPS"]:
+            if f not in ["RGB_Gen", "Instance_Mask", "Models", "Pose_transformed", "Bbox", "FPS"]:
                 os.mkdir(f"{name}/{f}")
             else:
-                os.makedirs(f"{name}/{f}/banana1")
-                os.makedirs(f"{name}/{f}/orange2")
-                os.makedirs(f"{name}/{f}/pear2")
+                os.makedirs(f"{name}/Generated/{f}/banana1")
+                os.makedirs(f"{name}/Generated/{f}/orange2")
+                os.makedirs(f"{name}/Generated/{f}/pear2")
 
 
 
@@ -189,8 +189,6 @@ if __name__ == '__main__':
 
     # futur parameters : 
 
-
-
     Categories = [] # to read
     Nb_instance = 1
     Occ_target = 0.5
@@ -202,18 +200,12 @@ if __name__ == '__main__':
 
     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",
                     "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)
@@ -224,7 +216,7 @@ if __name__ == '__main__':
     list_obj = ["banana1", "orange2", "pear2"]
     for obj in list_obj:
         src_bbox = f"Models/{obj}/{obj.lower()}.ply"
-        dst_bbox = f"{dataset_name}/Models/{obj}/{obj.lower()}.ply"
+        dst_bbox = f"{dataset_name}/Generated/Models/{obj}/{obj.lower()}.ply"
         shutil.copy(src_bbox, dst_bbox)
 
     if choice == 'high':
@@ -236,7 +228,7 @@ if __name__ == '__main__':
                             [0.0, 1086.5054444841007, 360.5],
                             [0.0, 0.0, 1.0]])
 
-    np.savetxt(f'{dataset_name}/camera_{choice}.txt', camera)
+    np.savetxt(f'{dataset_name}/Generated/camera_{choice}.txt', camera)
 
     # frame = "1_600000000"
     frame = "1_926000000"
@@ -244,10 +236,8 @@ 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, True)
+    generate_fps(dataset_name, camera, Nb_camera, Nb_world, list_obj, False)
     #generate_3d_bbox(dataset_name)

pose.py

@@ -113,7 +113,7 @@ def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
                     T_exp = transformation @ xyz
                     T_exp = np.array(T_exp)
                     num_arr = np.c_[R_exp, T_exp[0]]
-                    np.save(f'{data_name}/Pose_transformed/banana1/{p}.npy', num_arr)  # save
+                    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
@@ -126,7 +126,7 @@ def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
                     T_exp = transformation @ xyz
                     T_exp = np.array(T_exp)
                     num_arr = np.c_[R_exp, T_exp[0]]
-                    np.save(f'{data_name}/Pose_transformed/orange2/{p}.npy', num_arr)  # save
+                    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
@@ -139,7 +139,7 @@ def transform_pose(data_name, Nb_camera, Nb_world, occ_target):
                     T_exp = transformation @ xyz
                     T_exp = np.array(T_exp)
                     num_arr = np.c_[R_exp, T_exp[0]]
-                    np.save(f'{data_name}/Pose_transformed/pear2/{p}.npy', num_arr)  # save
+                    np.save(f'{data_name}/Generated/Pose_transformed/pear2/{p}.npy', num_arr)  # save
                 else:
                     continue
     print(cont1, cont2, cont3)