Updated code to keep it running on Ubuntu 22.04 / python 3.10.12 / March 2024

Makefile

@@ -1,10 +1,10 @@
 all:
     # install pycocotools locally
 	pip install -r requirements.txt
-	python setup.py build_ext --inplace
+	python3 setup.py build_ext --inplace
 	rm -rf build
 
 install:
 	# install pycocotools to the Python site-packages
-	python setup.py build_ext install
-	rm -rf build
+	python3 setup.py build_ext install
+	rm -rf build

README.md

@@ -26,12 +26,12 @@ Use the Makefile to install the coco-analyze api:
 ### Usage
 To run the extended multi-instance keypoint estimation error analysis: update the paths of the detections and annotations and execute the command line.
 
-    [annFile]  -> ./annotations/keypoints_val2014.json
+    [annFile]  -> ./annotations/person_keypoints_val2014.json
     [dtsFile]  -> ./detections/fakekeypoints100_keypoints_val2014_results.json
     [saveDir]  -> ./results/fakekeypoints100
     [teamName] -> fakekeypoints100
     [version]  -> 1.0
-    $ python run_analysis.py [annFile] [dtsFile] [saveDir] [teamName] [version]
+    $ python3 run_analysis.py [annFile] [dtsFile] [saveDir] [teamName] [version]
 
 ### Results
  - A summary file called `[teamName]_performance_report.tex` will be created once the analysis is complete.

analysisAPI/backgroundFalseNegErrors.py

@@ -3,7 +3,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.path as mplPath
-from scipy.misc import imresize
+#from scipy.misc import imresize
+from skimage.transform import resize as imresize
 import skimage.io as io
 
 # package imports 

analysisAPI/backgroundFalsePosErrors.py

@@ -3,7 +3,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.path as mplPath
-from scipy.misc import imresize
+#from scipy.misc import imresize
+from skimage.transform import resize as imresize
 import skimage.io as io
 
 # package imports 

analysisAPI/utilities.py

@@ -6,7 +6,8 @@
 import matplotlib.path as mplPath
 from matplotlib.collections import PatchCollection
 from matplotlib.patches import Polygon
-from scipy.misc import imresize
+#from scipy.misc import imresize
+from skimage.transform import resize as imresize
 import skimage.io as io
 
 """

pycocotools/cocoeval.py

@@ -447,6 +447,7 @@ def accumulate(self, p = None):
                     tps = np.logical_and(               dtm,  np.logical_not(dtIg) )
                     fps = np.logical_and(np.logical_not(dtm), np.logical_not(dtIg) )
 
+                    np.float = float  #For Numpy > 1.20
                     tp_sum = np.cumsum(tps, axis=1).astype(dtype=np.float)
                     fp_sum = np.cumsum(fps, axis=1).astype(dtype=np.float)
                     for t, (tp, fp) in enumerate(zip(tp_sum, fp_sum)):
@@ -616,8 +617,13 @@ def setKpParams(self):
         self.imgIds = []
         self.catIds = []
         # np.arange causes trouble.  the data point on arange is slightly larger than the true value
-        self.iouThrs = np.linspace(.5, 0.95, np.round((0.95 - .5) / .05) + 1, endpoint=True)
-        self.recThrs = np.linspace(.0, 1.00, np.round((1.00 - .0) / .01) + 1, endpoint=True)
+        #Switch from :
+        #self.iouThrs = np.linspace(.5, 0.95, np.round((0.95 - .5) / .05) + 1, endpoint=True)
+        #self.recThrs = np.linspace(.0, 1.00, np.round((1.00 - .0) / .01) + 1, endpoint=True)
+        #To :
+        self.iouThrs = np.linspace(.5, 0.95, int(np.round((0.95 - .5) / .05) + 1), endpoint=True)
+        self.recThrs = np.linspace(.0, 1.00, int(np.round((1.00 - .0) / .01) + 1), endpoint=True)
+        #Using this advice : https://github.com/matteorr/coco-analyze/issues/28 
         self.maxDets = [20]
         self.areaRng = [[0 ** 2, 1e5 ** 2], [32 ** 2, 96 ** 2], [96 ** 2, 1e5 ** 2]]
         self.areaRngLbl = ['all', 'medium', 'large']

requirements.txt

@@ -1,3 +1,8 @@
+pillow
+cython
+scipy
 colour
 numpy
-matplotlib
+matplotlib
+jinja2
+scikit-image