update opencv version to 4.4.0

Detectors/HandcraftDetector.py

@@ -44,7 +44,11 @@ def __init__(self, config={}):
                                       fastThreshold=self.config["ORB"]["fastThreshold"])
         elif self.config["type"] == "SIFT":
             logging.info("creating SIFT detector...")
-            self.det = cv2.xfeatures2d.SIFT_create(nfeatures=self.config["SIFT"]["nfeatures"],
+            if cv2.__version__ < '4.4.0':
+                SIFT_create = cv2.xfeatures2d.SIFT_create
+            else:
+                SIFT_create = cv2.SIFT_create
+            self.det = cv2.SIFT_create(nfeatures=self.config["SIFT"]["nfeatures"],
                                                    nOctaveLayers=self.config["SIFT"]["nOctaveLayers"],
                                                    contrastThreshold=self.config["SIFT"]["contrastThreshold"],
                                                    edgeThreshold=self.config["SIFT"]["edgeThreshold"],

readme.md

@@ -46,16 +46,6 @@ For feature matchers, we tested the KNN and FLANN mathers implemented in OpenCV,
     pip install -r requirements.txt
     ```
 
-- Build and install OpenCV from source with opencv-contrib and flag `OPENCV_ENABLE_NONFREE=True`
-    ```bash
-    git clone https://github.com/opencv/opencv.git
-    git clone https://github.com/opencv/opencv_contrib.git
-    cd opencv
-    mkdir build && cd build
-    cmake .. -DOPENCV_EXTRA_MODULE_PATH=../../opencv_contrib/modules -DOPENCV_ENABLE_NONFREE=True
-    make -j4 install 
-    ```
-
 ## Run
 1. edit dataset path in `params/*.yaml`;
 2. run `python main.py --config params/*.yaml` in terminal.

requirements.txt

@@ -2,4 +2,5 @@ numpy~=1.18.3
 torch~=1.5.0
 matplotlib~=2.1.1
 PyYAML>=4.2b1
-tqdm~=4.47.0
+tqdm~=4.47.0
+opencv-python~=4.4.0