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diff --git a/03nov/image_test.jpg b/03nov/image_test.jpg
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diff --git a/03nov/main.py b/03nov/main.py
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+from umage import load, save, show_image
+
+def grayscale(img_mat):
+    """Transform an image into gray
+
+    :img_mat: image en entree
+    :returns: grayscale de limage em entree
+
+    """
+    new_matrix = list()
+    for row in range(len(img_mat)):
+        new_matrix.append(list())
+        for column in img_mat[row]:
+            _r, _g, _b = column
+            gray = round(0.2125 * _r + 0.7154 * _g + 0.0721 * _b)
+            new_matrix[row].append((gray, gray, gray))
+
+    return new_matrix
+
+def convolution(img_mat, mat):
+    """effectue le passage d'une matrice de convolution sur une image grise
+    TODO: image de couleurs
+
+    :img_mat: image en entree
+    :mat: matrice de convolution
+    :returns: image retouchee
+
+    """
+
+    new_matrix = list()
+    for row in range(len(img_mat)):
+        new_matrix.append(list())
+        for column in range(len(img_mat[row])):
+            # _gray = img_mat[row][column][0]
+            _sum = 0
+            for mat_row in range(len(mat)):
+                for mat_column in range(len(mat[mat_row])):
+                    diff_row = mat_row - len(mat)//2
+                    diff_col = mat_column - len(mat[mat_column])//2
+                    if dans_image(img_mat, row+diff_row, column+ diff_col):
+                        _sum += mat[mat_row][mat_column] * img_mat[row + diff_row][column + diff_col][0]
+            new_matrix[row].append((_sum, _sum, _sum))
+    return new_matrix
+
+def dans_image(img_mat, row, col):
+    if row < len(img_mat)-1 and row > 0 and col < len(img_mat[0])-1 and col > 0:
+        return True
+    return False
+
+if __name__ == "__main__":
+    unit = [
+            [0, 1, 0],
+            [0, 0, 0],
+            [0, 0, 0]]
+    convolution1 = [
+            [-1, -1, -1],
+            [-1,  8, -1],
+            [-1, -1, -1]]
+    convolution2 = [
+            [-1, -1, -1],
+            [-1,  9, -1],
+            [-1, -1, -1]]
+    convolution3 = [
+            [-2, 0, 0],
+            [ 0, 1, 0],
+            [ 0, 0, 2]]
+    img = load('./myimg.jpg')
+    new_image = grayscale(img)
+    convolution(new_image, convolution2)
+    save(new_image, 'gray')
+    save(convolution(new_image, convolution1), 'convo1')
+    save(convolution(new_image, convolution2), 'convo2')
+    save(convolution(new_image, convolution3), 'convo3')
diff --git a/03nov/myimg.jpg b/03nov/myimg.jpg
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diff --git a/03nov/serie7.pdf b/03nov/serie7.pdf
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diff --git a/03nov/traceback.txt b/03nov/traceback.txt
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+Traceback (most recent call last):
+  File "/home/tonitch/.local/lib/python3.10/site-packages/pudb/__init__.py", line 148, in runscript
+    dbg._runscript(mainpyfile)
+  File "/home/tonitch/.local/lib/python3.10/site-packages/pudb/debugger.py", line 519, in _runscript
+    self.run(statement)
+  File "/usr/lib/python3.10/bdb.py", line 597, in run
+    exec(cmd, globals, locals)
+  File "<string>", line 1, in <module>
+  File "main.py", line 65, in <module>
+    final_img = convolution(new_image, unit)
+  File "main.py", line 41, in convolution
+    _sum += mat[mat_row][mat_column] * img_mat[row + diff_row][column + diff_col][0]
+IndexError: list index out of range
diff --git a/03nov/umage.py b/03nov/umage.py
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+++ b/03nov/umage.py
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+#!/usr/bin/env python3
+
+from PIL import Image  # Requires python-image-library (pillow)
+import itertools
+
+
+def load(filename):
+    """ Given a filename that matches an image file,
+    return a list of lists of tuples corresponding to the list of
+    lines of pixels (R, G, B) of the image. """
+
+    with Image.open(filename, 'r') as image:
+        image = image.convert('RGB')
+        content = list(image.getdata())
+        size_x, size_y = image.size
+        return [content[i:i + size_x] for i in range(0, len(content), size_x)]
+
+
+def save(image, filename='new', extension='jpg'):
+    """ Stores the given image into a file. The name
+    of the file is set to <filename>.<extension> which is
+    'new.jpg' by default. """
+
+    size_x, size_y = len(image), len(image[0])
+    new_image = Image.new('RGB', (size_y, size_x))
+    new_image.putdata(list(itertools.chain.from_iterable(image)))
+    new_image.save('%s.%s' % (filename, extension))
+
+def show_image(image):
+    """ Show the image to the user. """
+
+    size_x, size_y = len(image), len(image[0])
+    new_image = Image.new('RGB', (size_y, size_x))
+    new_image.putdata(list(itertools.chain.from_iterable(image)))
+    new_image.show()