1 files changed, 0 insertions, 82 deletions
diff --git a/notebooks/utils/imx.py b/notebooks/utils/imx.py
deleted file mode 100644
index 0dbdcf7e..00000000
--- a/notebooks/utils/imx.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import os
-from os.path import join
-import cv2
-
-from PIL import Image, ImageDraw
-import matplotlib.pyplot as plt
-
-
-def ensure_pil(im):
-    """Ensure image is Pillow format"""
-    try:
-        im.verify()
-        return im
-    except:
-        return Image.fromarray(im.astype('uint8'), 'RGB')
-
-def ensure_np(im):
-    """Ensure image is numpy array"""
-    if type(im) == np.ndarray:
-        return im
-    return np.asarray(im, np.uint8)
-
-def ensure_dir(d):
-    """Create directories"""
-    if not os.path.exists(d):
-        os.makedirs(d)
-
-def filter_pixellate(src,num_cells):
-    """Downsample, then upsample image for pixellation"""
-    w,h = src.size
-    dst = src.resize((num_cells,num_cells), Image.NEAREST)
-    dst = dst.resize((w,h), Image.NEAREST)
-    return dst
-
-# Plot images inline using Matplotlib
-def pltimg(im,title=None,mode='rgb',figsize=(8,12),dpi=160,output=None):
-    plt.figure(figsize=figsize)
-    plt.xticks([]),plt.yticks([])
-    if title is not None:
-        plt.title(title)
-    if mode.lower() == 'bgr':
-        im = cv2.cvtColor(im,cv2.COLOR_BGR2RGB)
-    f = plt.gcf()
-    plt.imshow(im)
-    plt.show()
-    plt.draw()
-    if output is not None:
-        bbox_inches='tight'
-        ext=osp.splitext(output)[1].replace('.','')
-        f.savefig(output,dpi=dpi,format=ext)
-        print('Image saved to: {}'.format(output))
-
-
-# Define a function to detect faces using OpenCV's haarcascades
-def detect_faces(classifier,src,scale_factor=1.1,overlaps=3,
-                min_size=70, max_size=700,
-                flags=0):
-    
-    min_size = (min_size, min_size) # minimum face size
-    max_size = (max_size, max_size) # maximum face size
-    
-    # Convert to grayscale
-    src_gray = cv2.cvtColor(src,cv2.COLOR_BGR2GRAY)
-    
-    # Run detector
-    matches = classifier.detectMultiScale(src_gray, 
-                                          scale_factor, 
-                                          overlaps, 
-                                          flags, 
-                                          min_size, 
-                                          max_size)
-    # By default, this returns x,y,w,w
-    # Modify to return x1,y1,x2,y2
-    matches = [ (r[0],r[1],r[0]+r[2],r[1]+r[3]) for r in matches]
-    
-    return matches
-
-def detect_faces_dlib(im,pyramids=0):
-    rects = detector(im, pyramids)
-    faces = [ (r.left(),r.top(),r.right(),r.bottom()) for r in rects] #x1,y1,x2,y2
-    return faces
-    
-\ No newline at end of file