optimising FPS too

compute_features.py

@@ -10,9 +10,11 @@ from bbox_2d import bbox_2d
 import cv2
 from instance_mask import instance
 from pose import convert2
+from matplotlib import image
+from fps_alg import process2
 
 
-def process_compute(data_name, Nb_camera, Nb_world, list_categories, occ_target):
+def process_compute(data_name, camera, Nb_camera, Nb_world, list_categories, occ_target, vis):
     transformation = np.matrix([[0.0000000, -1.0000000, 0.0000000],
                                 [0.0000000, 0.0000000, -1.0000000],
                                 [1.0000000, 0.0000000, 0.0000000]])
@@ -31,7 +33,7 @@ def process_compute(data_name, Nb_camera, Nb_world, list_categories, occ_target)
             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))
+                #print("len(data)", len(data_3D_pose))
 
             ### 2D BBox ###
             with open(f"{data_name}/Bbox_2d/{p}.json", 'r') as f:
@@ -75,6 +77,36 @@ def process_compute(data_name, Nb_camera, Nb_world, list_categories, occ_target)
                     instance_img = instance(img, id)
                     cv2.imwrite(f"{data_name}/Generated/Instance_Mask/{categories}/{p}.png", 255*instance_img)
 
+
+                    img = image.imread(f"{data_name}/RGB/{p}.png")
+
+                    np.set_printoptions(precision=15)
+                    pose = np.load(f'{data_name}/Generated/Pose_transformed/{categories}/{p}.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]])
+
+                    
+                    fps_points = np.loadtxt(f'{data_name}/Generated/FPS/{categories}_fps_3d.txt')
+                    # process(pcd_bbox, pcd, R_exp, tVec, camera, img)
+                    points = process2(fps_points, R_exp, tVec, camera, img, vis)
+                    out = np.zeros((1, 401))
+
+                    out[0] = catergories_occ_array[categories] #obj_id #len have to be 1 !!
+                    ind = 1
+                    for point in points:
+                        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}/Generated/FPS/{categories}/{p}.txt', out)
+                    #print("stop")
+
+
     print(cont1, cont2, cont3)
 
 

fps_alg.py

@@ -97,29 +97,15 @@ def apply_fps(pcd, fps_num):
 
 def process2(pcd, R_exp, tVec, camera, img, vis= True):
 
-    # point_cloud_in_numpy = np.asarray(pcd.points)
-    # center = point_cloud_in_numpy.mean(0)
-    #
-    # new_point = fps(point_cloud_in_numpy, center, fps_num)
-    # print(new_point)
-
-    # pcd_fps = o3d.geometry.PointCloud()
-    # 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'))
 
-    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))
@@ -195,11 +181,11 @@ def generate_fps(data_name, camera, Nb_camera, Nb_world, list_categories, occ_ta
 
                     np.set_printoptions(precision=15)
                     pose = np.load(f'{data_name}/Generated/Pose_transformed/{categories}/{p}.npy')
-                    print(pose)
+                    #print(pose)
                     R_exp = pose[0:3, 0:3]
                     tVec = pose[0:3, 3]
 
-                    print(tVec)
+                    #print(tVec)
                     # camera = np.matrix([[1386.4138492513919, 0.0, 960.5],
                     #                     [0.0, 1386.4138492513919, 540.5],
                     #                     [0.0, 0.0, 1.0]])

main.py

@@ -5,7 +5,7 @@ from prepare_data import reform_data
 #from pose import transform_pose
 #from bbox_2d import generate_2d_bbox
 #from instance_mask import generate_instance_mask
-from fps_alg import generate_fps, apply_fps
+from fps_alg import apply_fps
 from bbox_3d import generate_3d_bbox
 from compute_features import process_compute
 import shutil
@@ -54,7 +54,7 @@ if __name__ == '__main__':
         point_cloud = f'{dataset_name}/Generated/Models/{categories}/{categories.lower()}.ply'
         pcd = o3d.io.read_point_cloud(point_cloud)
 
-        print("pcd", pcd)
+        #print("pcd", pcd)
 
         fps_points = apply_fps(pcd, 200)
         #print(fps_points)
@@ -74,9 +74,9 @@ if __name__ == '__main__':
 
     reform_data(dataset_src, dataset_name, dataset_type, frame, Nb_camera, Nb_world)
 
-    process_compute(dataset_name, Nb_camera, Nb_world, list_categories, occ_target)
+    process_compute(dataset_name, camera, Nb_camera, Nb_world, list_categories, occ_target, 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, occ_target, True)
+    #generate_fps(dataset_name, camera, Nb_camera, Nb_world, list_categories, occ_target, True)
     #generate_3d_bbox(dataset_name)