finish ex3

ex3.py

@@ -1,13 +1,14 @@
 import os.path
 from glob import glob
 
+import numpy as np
+from PIL import Image, ImageStat
+
 
 class ImageStandardizer:
     def __init__(self, input_dir: str) -> None:
         super().__init__()
 
-        # todo scan for .jpeg files
-
         # scan input dir for files
         files = glob(input_dir + '/**/*.jpg', recursive=True)
         if len(files) == 0:
@@ -19,8 +20,47 @@ class ImageStandardizer:
         # sort filenames
         files.sort()
 
-    def analyze_images(self) -> None:
+        self.files = files
-        pass
+        self.mean = None
+        self.std = None
 
-    def get_standardized_images(self) -> None:
+    def analyze_images(self) -> (np.array, np.array):
-        pass
+        mymean = np.zeros((3,), dtype=np.float64)
+        mystd = np.zeros((3,), dtype=np.float64)
+
+        for file in self.files:
+            img = Image.open(file)
+            stats = ImageStat.Stat(img)
+            mymean += stats.mean
+            mystd += stats.stddev
+
+            del img
+
+        mymean /= len(self.files)
+        mystd /= len(self.files)
+
+        self.mean = mymean
+        self.std = mystd
+
+        return mymean, mystd
+
+    def get_standardized_images(self):
+        if self.mean is None or self.std is None:
+            raise ValueError
+
+        for file in self.files:
+            img = Image.open(file)
+            arr = np.asarray(img.getdata(), dtype=np.float32).reshape(
+                (img.height, img.width, 3))  # and reshape into 3channel rgb image
+            # standardize image
+            arr = (arr - self.mean) / self.std
+            yield np.array(arr, dtype=np.float32)
+
+
+# Press the green button in the gutter to run the script.
+if __name__ == '__main__':
+    std = ImageStandardizer(input_dir='unittest/unittest_input_0')
+    print(std.analyze_images())
+
+    for i in std.get_standardized_images():
+        print(i)

ex3_unittest.py

@@ -0,0 +1,204 @@
+"""
+Author -- Michael Widrich, Andreas Schörgenhumer
+Contact -- schoergenhumer@ml.jku.at
+Date -- 02.03.2022
+
+###############################################################################
+
+The following copyright statement applies to all code within this file.
+
+Copyright statement:
+This  material,  no  matter  whether  in  printed  or  electronic  form,
+may  be  used  for personal  and non-commercial educational use only.
+Any reproduction of this manuscript, no matter whether as a whole or in parts,
+no matter whether in printed or in electronic form, requires explicit prior
+acceptance of the authors.
+
+###############################################################################
+
+Images taken from: https://pixabay.com/
+"""
+
+import gzip
+import os
+import signal
+import sys
+from glob import glob
+from types import GeneratorType
+
+import dill as pkl
+import numpy as np
+
+
+def print_outs(outs, line_token="-"):
+    print(line_token * 40)
+    print(outs, end="" if isinstance(outs, str) and outs.endswith("\n") else "\n")
+    print(line_token * 40)
+
+
+time_given = int(15)
+
+check_for_timeout = hasattr(signal, "SIGALRM")
+
+if check_for_timeout:
+    def handler(signum, frame):
+        raise TimeoutError(f"Timeout after {time_given}sec")
+    
+    
+    signal.signal(signal.SIGALRM, handler)
+
+ex_file = "ex3.py"
+full_points = 15
+points = full_points
+python = sys.executable
+
+inputs = sorted(glob(os.path.join("unittest", "unittest_input_*"), recursive=True))
+
+if not len(inputs):
+    raise FileNotFoundError("Could not find unittest_input_* files")
+
+for test_i, input_folder in enumerate(inputs):
+    comment = ""
+    fcall = ""
+    
+    with open(os.devnull, "w") as null:
+        # sys.stdout = null
+        try:
+            if check_for_timeout:
+                signal.alarm(time_given)
+                from ex3 import ImageStandardizer
+                
+                signal.alarm(0)
+            else:
+                from ex3 import ImageStandardizer
+            proper_import = True
+        except Exception as e:
+            errs = e
+            points -= full_points / len(inputs)
+            proper_import = False
+        finally:
+            sys.stdout.flush()
+            sys.stdout = sys.__stdout__
+    
+    if proper_import:
+        with open(os.devnull, "w") as null:
+            # sys.stdout = null
+            try:
+                if check_for_timeout:
+                    signal.alarm(time_given)
+                    # check constructor
+                    instance = ImageStandardizer(input_dir=input_folder)
+                    fcall = f"ImageStandardizer(input_dir='{input_folder}')"
+                    signal.alarm(0)
+                else:
+                    # check constructor
+                    instance = ImageStandardizer(input_dir=input_folder)
+                    fcall = f"ImageStandardizer(input_dir='{input_folder}')"
+                errs = ""
+                
+                # check correct file names + sorting
+                input_basename = os.path.basename(input_folder)
+                with open(os.path.join("unittest", "solutions", input_basename, f"filenames.txt"), "r") as f:
+                    # must replace the separator that was used when creating the solution files
+                    files_sol = f.read().replace("\\", os.path.sep).splitlines()
+                    # for simplicity's sake, only compare relative paths here
+                    common = os.path.commonprefix(instance.files)
+                    rel_instance_files = [os.path.join(input_folder, f[len(common):]) for f in instance.files]
+                    if not hasattr(instance, "files"):
+                        points -= full_points / len(inputs) / 3
+                        comment += f"Attributes 'files' missing.\n"
+                    elif rel_instance_files != files_sol:
+                        points -= full_points / len(inputs) / 3
+                        comment += f"Attribute 'files' should be {files_sol} but is {instance.files} (see directory 'solutions').\n"
+                    elif len(instance.files) != len(files_sol):
+                        points -= full_points / len(inputs) / 3
+                        comment += f"Number of files should be {len(files_sol)} but is {len(instance.files)} (see directory 'solutions').\n"
+                
+                # check if class has method analyze_images
+                method = "analyze_images"
+                if not hasattr(instance, method):
+                    comment += f"Method '{method}' missing.\n"
+                    points -= full_points / len(inputs) / 3
+                else:
+                    # check for correct data types
+                    stats = instance.analyze_images()
+                    if (type(stats) is not tuple) or (len(stats) != 2):
+                        points -= full_points / len(inputs) / 3
+                        comment += f"Incorrect return value of method '{method}' (should be tuple of length 2).\n"
+                    else:
+                        with open(os.path.join("unittest", "solutions", input_basename, f"mean_and_std.pkl"),
+                                  "rb") as fh:
+                            data = pkl.load(fh)
+                            m = data["mean"]
+                            s = data["std"]
+                        if not (isinstance(stats[0], np.ndarray) and isinstance(stats[1], np.ndarray) and
+                                stats[0].dtype == np.float64 and stats[1].dtype == np.float64 and
+                                stats[0].shape == (3,) and stats[1].shape == (3,)):
+                            points -= full_points / len(inputs) / 3
+                            comment += f"Incorrect return data type of method '{method}' (tuple entries should be np.ndarray of dtype np.float64 and shape (3,)).\n"
+                        else:
+                            if not np.isclose(stats[0], m, atol=0).all():
+                                points -= full_points / len(inputs) / 6
+                                comment += f"Mean should be {m} but is {stats[0]} (see directory 'solutions').\n"
+                            if not np.isclose(stats[1], s, atol=0).all():
+                                points -= full_points / len(inputs) / 6
+                                comment += f"Std should be {s} but is {stats[1]} (see directory 'solutions').\n"
+                
+                # check if class has method get_standardized_images
+                method = "get_standardized_images"
+                if not hasattr(instance, method):
+                    comment += f"Method '{method}' missing.\n"
+                    points -= full_points / len(inputs) / 3
+                # check for correct data types
+                elif not isinstance(instance.get_standardized_images(), GeneratorType):
+                    points -= full_points / len(inputs) / 3
+                    comment += f"'{method}' is not a generator.\n"
+                else:
+                    # Read correct image solutions
+                    with gzip.open(os.path.join("unittest", "solutions", input_basename, "images.pkl"), "rb") as fh:
+                        ims_sol = pkl.load(file=fh)
+                    
+                    # Get image submissions
+                    ims_sub = list(instance.get_standardized_images())
+                    
+                    if not len(ims_sub) == len(ims_sol):
+                        points -= full_points / len(inputs) / 3
+                        comment += f"{len(ims_sol)} image arrays should have been returned but got {len(ims_sub)}.\n"
+                    elif any([im_sub.dtype.num != np.dtype(np.float32).num for im_sub in ims_sub]):
+                        points -= full_points / len(inputs) / 3
+                        comment += f"Returned image arrays should have datatype np.float32 but at least one array isn't.\n"
+                    else:
+                        equal = [np.all(np.isclose(im_sub, im_sol, atol=0)) for im_sub, im_sol in zip(ims_sub, ims_sol)]
+                        if not all(equal):
+                            points -= full_points / len(inputs) / 3
+                            comment += f"Returned images {list(np.where(np.logical_not(equal))[0])} do not match solution (see images.pkl files for solution).\n"
+            except Exception as e:
+                errs = e
+                points -= full_points / len(inputs)
+            finally:
+                sys.stdout.flush()
+                sys.stdout = sys.__stdout__
+    
+    print()
+    print_outs(f"Test {test_i}", line_token="#")
+    print("Function call:")
+    print_outs(fcall)
+    
+    if errs:
+        print(f"Some unexpected errors occurred:")
+        print_outs(f"{type(errs).__name__}: {errs}")
+    else:
+        print("Notes:")
+        print_outs("No issues found" if comment == "" else comment)
+        
+    # due to floating point calculations it could happen that we get -0 here
+    if points < 0:
+        assert abs(points) < 1e-7, f"points were {points} < 0: error when subtracting points?"
+        points = abs(points)
+    print(f"Current points: {points:.2f}")
+
+print(f"\nEstimated points upon submission: {points:.2f} (out of {full_points:.2f})")
+print(f"This is only an estimate, see 'Instructions for submitting homework' in Moodle "
+      f"for common mistakes that can still lead to 0 points.")
+if not check_for_timeout:
+    print("\n!!Warning: Had to switch to Windows compatibility version and did not check for timeouts!!")

unittest/solutions/unittest_input_0/filenames.txt

@@ -0,0 +1,7 @@
+unittest\unittest_input_0\00.jpg
+unittest\unittest_input_0\01.jpg
+unittest\unittest_input_0\02.jpg
+unittest\unittest_input_0\04.jpg
+unittest\unittest_input_0\05.jpg
+unittest\unittest_input_0\subfolder\06.jpg
+unittest\unittest_input_0\subfolder\07.jpg

unittest/solutions/unittest_input_1/filenames.txt

@@ -0,0 +1,9 @@
+unittest\unittest_input_1\08.jpg
+unittest\unittest_input_1\09.jpg
+unittest\unittest_input_1\11.jpg
+unittest\unittest_input_1\12.jpg
+unittest\unittest_input_1\13.jpg
+unittest\unittest_input_1\14.jpg
+unittest\unittest_input_1\subfolder\15.jpg
+unittest\unittest_input_1\subfolder\subsubfolder\16.jpg
+unittest\unittest_input_1\subfolder\subsubfolder\17.jpg