Merge "Cleanup of warnings from y2020 python code"
diff --git a/y2020/vision/tools/python_code/train_and_match.py b/y2020/vision/tools/python_code/train_and_match.py
index 6250da1..ca67095 100644
--- a/y2020/vision/tools/python_code/train_and_match.py
+++ b/y2020/vision/tools/python_code/train_and_match.py
@@ -52,13 +52,13 @@
# Load feature extractor based on extractor name
# Returns feature extractor object
def load_feature_extractor():
- if FEATURE_EXTRACTOR_NAME is 'SIFT':
+ if FEATURE_EXTRACTOR_NAME == 'SIFT':
# Initiate SIFT detector
feature_extractor = cv2.SIFT_create()
- elif FEATURE_EXTRACTOR_NAME is 'SURF':
+ elif FEATURE_EXTRACTOR_NAME == 'SURF':
# Initiate SURF detector
feature_extractor = cv2.xfeatures2d.SURF_create()
- elif FEATURE_EXTRACTOR_NAME is 'ORB':
+ elif FEATURE_EXTRACTOR_NAME == 'ORB':
# Initiate ORB detector
feature_extractor = cv2.ORB_create()
@@ -78,7 +78,7 @@
kp, des = feature_extractor.detectAndCompute(image_list[i], None)
descriptor_lists.append(des)
keypoint_lists.append(kp)
- elif FEATURE_EXTRACTOR_NAME is 'ORB':
+ elif FEATURE_EXTRACTOR_NAME == 'ORB':
# TODO: Check whether ORB extractor can do detectAndCompute.
# If so, we don't need to have this branch for ORB
for i in range(len(image_list)):
@@ -104,7 +104,7 @@
matcher = cv2.FlannBasedMatcher(index_params, search_params)
matcher.add(descriptor_lists)
matcher.train()
- elif FEATURE_EXTRACTOR_NAME is 'ORB':
+ elif FEATURE_EXTRACTOR_NAME == 'ORB':
# Use FLANN LSH for ORB
FLANN_INDEX_LSH = 6
index_params = dict(
@@ -144,7 +144,7 @@
good_matches_list.append(good_matches)
- elif FEATURE_EXTRACTOR_NAME is 'ORB':
+ elif FEATURE_EXTRACTOR_NAME == 'ORB':
matches = matcher.knnMatch(train_keypoint_lists[0], desc_query, k=2)
good_matches = []
for m in matches: