Porting hazen to python 3.9

environment.yml

@@ -0,0 +1,47 @@
+name: hazen-3.9-miniforge
+
+dependencies:
+  - pip=21.3.1
+  - python=3.9.7
+  - scikit-image
+  - psycopg2-binary
+  - pip:
+    - SQLAlchemy_Utils==0.33.11
+    - alembic==1.0.10
+    - celery==4.3.1
+    - numpy==1.21.0
+    - Werkzeug==0.15.4
+    - opencv-python==4.5.4.58
+    - Flask_Migrate==2.5.1
+    - pytest>=6.2
+    - coverage>=6.0.2
+    - Flask_Moment==0.7.0
+    - flask_heroku==0.1.9
+    - Flask==1.0.3
+    - pydicom==1.4.1
+    - WTForms==2.2.1
+    - Flask_Dropzone==1.5.3
+    - Flask_Mail==0.9.1
+    - Flask_Login==0.4.1
+    - Flask_Bootstrap4==4.0.2
+    - imutils==0.5.3
+    - matplotlib==3.4.3
+    - Flask_SQLAlchemy==2.4.0
+    - scipy==1.7.2
+    - docopt==0.6.2
+    - SQLAlchemy==1.3.3
+    - Flask_WTF==0.14.2
+    - flask_bootstrap==3.3.7.1
+    - PyJWT==1.7.1
+    - gunicorn==19.9.0
+#    - psycopg2-binary==2.8.4
+    - arrow==0.13.2
+    - amqp==2.4.2
+    - sphinxcontrib-needs==0.4.3
+    - sphinxcontrib-napoleon
+    - sphinx_rtd_theme
+    - m2r
+    - python-dateutil
+    - email_validator
+    - colorlog
+

hazenlib/slice_width.py

@@ -362,7 +362,7 @@ def get_initial_trapezoid_fit_and_coefficients(profile, slice_thickness):
         n_ramp = 47
         n_plateau = 55
 
-    trapezoid_centre = round(np.median(np.argwhere(profile < np.mean(profile)))).astype(int)
+    trapezoid_centre = int(round(np.median(np.argwhere(profile < np.mean(profile)))))
 
     n_total = len(profile)
     n_left_baseline = int(trapezoid_centre - round(n_plateau / 2) - n_ramp - 1)

hazenlib/spatial_resolution.py

@@ -174,9 +174,9 @@ def thresh_image(img, bound=150):
 
 
 def find_square(img):
-    cnts = cv.findContours(img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
+    cnts = cv.findContours(img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)[0]
 
-    for c in cnts[1]:
+    for c in cnts:
         perimeter = cv.arcLength(c, True)
         approx = cv.approxPolyDP(c, 0.1 * perimeter, True)
         if len(approx) == 4: