From 9c5d61baa3051b6f60d2ab7d53e17159da78f27c Mon Sep 17 00:00:00 2001
From: Gduret <guillaume.duret@ec-lyon.fr>
Date: Wed, 1 Mar 2023 16:02:35 +0100
Subject: [PATCH] add resizing fps
---
compute_features.py | 34 +++++++++++++++++++++++++++-------
fps_alg.py | 2 +-
main.py | 15 ++++++++++++---
3 files changed, 40 insertions(+), 11 deletions(-)
diff --git a/compute_features.py b/compute_features.py
index f2473af..af05403 100644
--- a/compute_features.py
+++ b/compute_features.py
@@ -31,7 +31,7 @@ def updateJsonFile():
jsonFile.close()
-def process_compute(data_name, camera, Nb_camera, World_begin, Nb_world, list_categories, occ_target, vis):
+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],
[0.0000000, 0.0000000, -1.0000000],
[1.0000000, 0.0000000, 0.0000000]])
@@ -66,9 +66,7 @@ def process_compute(data_name, camera, Nb_camera, World_begin, Nb_world, list_ca
for categories in list_categories:
-
if categories in catergories_occ_array.keys():
-
if len(catergories_occ_array[categories]) == 1 :
meta = {}
@@ -131,11 +129,15 @@ def process_compute(data_name, camera, Nb_camera, World_begin, Nb_world, list_ca
instance_img = instance(img, id)
cv2.imwrite(f"{data_name}/Generated/{categories}/Instance_Mask/{p}.png", 255*instance_img)
-
+ cat_mask = cv2.resize(instance_img, new_size)
+ cv2.imwrite(f"{data_name}/Generated/{categories}/Instance_Mask_resized/{p}.png", 255*cat_mask)
img = cv2.imread(f"{data_name}/RGB/{p}.png")
cv2.imwrite(f"{data_name}/Generated/{categories}/RGB_Gen/{p}.png", img)
+ img_resized = cv2.resize(img, new_size)
+ cv2.imwrite(f"{data_name}/Generated/{categories}/RGB_resized/{p}.png", img_resized)
+
np.set_printoptions(precision=15)
pose = np.load(f'{data_name}/Generated/{categories}/Pose_transformed/{p}.npy')
#print(pose)
@@ -170,12 +172,30 @@ def process_compute(data_name, camera, Nb_camera, World_begin, Nb_world, list_ca
out.append(x)
out.append(y)
ind += 2
- print("points" , points)
- print("out" , out)
- print("np.array(out).reshape(1, len(out))", np.array(out).reshape(1, len(out)))
+
np.savetxt(f'{data_name}/Generated/{categories}/FPS/{p}.txt', np.array(out).reshape(1, len(out)))
#print("stop")
+ points_resized = process2(fps_points, R_exp, tVec, camera_resized, img_resized, vis)
+ #out = np.zeros((1, ))
+
+ out_resized = [int(catergories_occ_array[categories][0])]# [catergories_occ_array[categories][0]] #obj_id #len have to be 1 !!
+ print(out)
+
+
+ ind_resized = 1
+ for point_resized in points_resized:
+ #out[0][ind] = point[0][0] / img.shape[1]
+ #[0][ind + 1] = point[0][1] / img.shape[0]
+ x_resized = point_resized[0][0] / img_resized.shape[1]
+ y_resized = point_resized[0][1] / img_resized.shape[0]
+ out_resized.append(x_resized)
+ out_resized.append(y_resized)
+ ind_resized += 2
+
+ np.savetxt(f'{data_name}/Generated/{categories}/FPS_resized/{p}.txt', np.array(out_resized).reshape(1, len(out_resized)))
+ #print("stop")
+
with open(f'{data_name}/Generated/Count_{p}.json', mode='w') as f:
f.write(json.dumps(list_count_categories, indent=4))
print(list_count_categories)
diff --git a/fps_alg.py b/fps_alg.py
index 3d5f14c..fa2f93f 100644
--- a/fps_alg.py
+++ b/fps_alg.py
@@ -108,13 +108,13 @@ def process2(pcd, R_exp, tVec, camera, img, vis= True):
# print(pcd_fps_numpy[n], '==>', keypoint_2d[0][n])
if vis:
+ img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
out = np.zeros((img.shape[0], img.shape[1], 16))
fig, ax = plt.subplots()
ax.imshow(img)
for n in range(len(pcd_fps_numpy)):
point = keypoint_2d[0][n]
ax.plot(point[0][0], point[0][1], marker='.', color="red")
-
plt.imshow(img)
plt.show()
return keypoint_2d[0]
diff --git a/main.py b/main.py
index ab43f89..421af84 100644
--- a/main.py
+++ b/main.py
@@ -17,11 +17,11 @@ def generate_folders(name, list_categories):
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", "Instance_Segmentation", "Semantic_Segmentation", "Instance_Mask", "Instance_Mask_resized", "Occlusion", "Models", "Pose_transformed", "Bbox", "FPS"]
+ folders = ["RGB", "RGB_Gen", "RGB_resized", "Meta_Gen", "Depth", "Mask", "Meta", "Pose", "Bbox_2d", "Bbox_2d_loose", "Instance_Segmentation", "Semantic_Segmentation", "Instance_Mask", "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", "Instance_Mask_resized", "Meta_Gen", "Models", "Pose_transformed", "Bbox", "FPS"]:
+ if f not in ["RGB_Gen", "RGB_resized", "Instance_Mask", "Instance_Mask_resized", "Meta_Gen", "Models", "Pose_transformed", "Bbox", "FPS" , "FPS_resized"]:
os.mkdir(f"{name}/{f}")
else:
for cat in list_categories:
@@ -74,6 +74,9 @@ if __name__ == '__main__':
np.savetxt(f'{dataset_name}/Generated/{categories}/{categories}_fps_3d.txt', fps_points)
+
+
+
if choice == 'high':
camera = np.matrix([[1386.4138492513919, 0.0, 960.5],
[0.0, 1386.4138492513919, 540.5],
@@ -85,11 +88,17 @@ if __name__ == '__main__':
new_size = (640, 480)
+ trans = np.matrix([[0.5, 0.0, 0.0],
+ [0.0, (2 / 3), 0.0],
+ [0.0, 0.0, 1.0]])
+
+ new_camera = trans @ camera
+
np.savetxt(f'{dataset_name}/Generated/camera_{choice}.txt', camera)
reform_data(dataset_src, dataset_name, dataset_type, Nb_camera, args.World_begin, args.Nb_worlds)
- process_compute(dataset_name, camera, new_size, Nb_camera, args.World_begin, args.Nb_worlds, list_categories, occ_target, False)
+ process_compute(dataset_name, camera, new_camera, new_size, Nb_camera, args.World_begin, args.Nb_worlds, list_categories, occ_target, True)
#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)
--
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