1 files changed, 82 insertions, 0 deletions
diff --git a/notebooks/utils/imx.py b/notebooks/utils/imx.py
new file mode 100644
index 00000000..0dbdcf7e
--- /dev/null
+++ b/notebooks/utils/imx.py
@@ -0,0 +1,82 @@
+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