update site, white

2 files changed, 45 insertions, 11 deletions

diff --git a/megapixels/app/utils/draw_utils.py b/megapixels/app/utils/draw_utils.py
index 7044a62f..1836768b 100644
--- a/megapixels/app/utils/draw_utils.py
+++ b/megapixels/app/utils/draw_utils.py
@@ -3,8 +3,10 @@ from math import sqrt
 
 import numpy as np
 import cv2 as cv
+import PIL
+from PIL import ImageDraw
 
-from app.utils import logger_utils
+from app.utils import logger_utils, im_utils
 
 log = logger_utils.Logger.getLogger()
 
@@ -118,6 +120,22 @@ def draw_landmarks2D(im, points_norm, radius=3, color=(0,255,0)):
     cv.circle(im_dst, pt, radius, color, -1, cv.LINE_AA)
   return im_dst
 
+def draw_landmarks2D_pil(im, points_norm, radius=3, color=(0,255,0)):
+  '''Draws facial landmarks, either 5pt or 68pt
+  '''
+  im_pil = im_utils.ensure_pil(im_utils.bgr2rgb(im))
+  draw = ImageDraw.Draw(im_pil)
+  dim = im.shape[:2][::-1]
+  for x,y in points_norm:
+    x1, y1 = (int(x*dim[0]), int(y*dim[1]))
+    xyxy = (x1, y1, x1+radius, y1+radius)
+    draw.ellipse(xyxy, fill='white')
+  del draw
+  im_dst = im_utils.ensure_np(im_pil)
+  im_dst = im_utils.rgb2bgr(im_dst)
+  return im_dst
+
+
 def draw_landmarks3D(im, points, radius=3, color=(0,255,0)):
   '''Draws 3D facial landmarks
   '''
@@ -126,12 +144,26 @@ def draw_landmarks3D(im, points, radius=3, color=(0,255,0)):
     cv.circle(im_dst, (x,y), radius, color, -1, cv.LINE_AA)
   return im_dst
 
-def draw_bbox(im, bbox_norm, color=(0,255,0), stroke_weight=2):
+def draw_bbox(im, bboxes_norm, color=(0,255,0), stroke_weight=2):
   '''Draws BBox onto cv image
+  :param color: RGB value
   '''
-  im_dst = im.copy()
-  bbox_dim = bbox_norm.to_dim(im.shape[:2][::-1])
-  cv.rectangle(im_dst, bbox_dim.pt_tl, bbox_dim.pt_br, color, stroke_weight, cv.LINE_AA)
+  #im_dst = im.copy()
+  if not type(bboxes_norm) == list:
+    bboxes_norm = [bboxes_norm]
+
+  im_pil = im_utils.ensure_pil(im_utils.bgr2rgb(im))
+  im_pil_draw = ImageDraw.ImageDraw(im_pil)
+
+  for bbox_norm in bboxes_norm:
+    bbox_dim = bbox_norm.to_dim(im.shape[:2][::-1])
+    #cv.rectangle(im_dst, bbox_dim.pt_tl, bbox_dim.pt_br, color, stroke_weight, cv.LINE_AA)
+    xyxy = (bbox_dim.pt_tl, bbox_dim.pt_br)  
+    im_pil_draw.rectangle(xyxy, outline=color, width=stroke_weight)
+    # draw.rectangle([x1, y1, x2, y2], outline=, width=3)
+  im_dst = im_utils.ensure_np(im_pil)
+  im_dst = im_utils.rgb2bgr(im_dst)
+  del im_pil_draw
   return im_dst
 
 def draw_pose(im, pt_nose, image_pts):
diff --git a/megapixels/app/utils/im_utils.py b/megapixels/app/utils/im_utils.py
index d36c1c32..670d5168 100644
--- a/megapixels/app/utils/im_utils.py
+++ b/megapixels/app/utils/im_utils.py
@@ -11,11 +11,6 @@ from skimage import feature
 import imutils
 import time
 import numpy as np
-import torch
-import torch.nn as nn
-import torchvision.models as models
-import torchvision.transforms as transforms
-from torch.autograd import Variable
 from sklearn.metrics.pairwise import cosine_similarity
 import datetime
 
@@ -293,6 +288,13 @@ def bgr2rgb(im):
   """
   return cv.cvtColor(im,cv.COLOR_BGR2RGB)
 
+def rgb2bgr(im):
+  """Wrapper for cv2.cvtColor transform
+    :param im: Numpy.ndarray (BGR)
+    :returns: Numpy.ndarray (RGB)
+  """
+  return cv.cvtColor(im,cv.COLOR_RGB2BGR)
+
 def compute_laplacian(im):
   # below 100 is usually blurry
   return cv.Laplacian(im, cv.CV_64F).var()
@@ -329,7 +331,7 @@ def normalizedGraylevelVariance(img):
     s = stdev[0]**2 / mean[0]
     return s[0]
 
-def compute_if_blank(im,width=100,sigma=0,thresh_canny=.1,thresh_mean=4,mask=None):
+def is_blank(im,width=100,sigma=0,thresh_canny=.1,thresh_mean=4,mask=None):
   # im is graysacale np
   #im = imutils.resize(im,width=width)
   #mask = imutils.resize(mask,width=width)