Move draw to utils

README.md

@@ -61,8 +61,7 @@ Identify people on images with face recognition as shown bellow.
 import os
 
 from abraia.faces import Recognition
-from abraia.utils import load_image, save_image
-from abraia.draw import render_results
+from abraia.utils import load_image, save_image, render_results
 
 img = load_image('images/rolling-stones.jpg')
 out = img.copy()
@@ -114,9 +113,8 @@ for k, frame in enumerate(video):
 Automatically recognize car license plates in images and video streams.
 
 ```python
-from abraia import draw
 from abraia.alpr import ALPR
-from abraia.utils import load_image, show_image
+from abraia.utils import load_image, show_image, render_results
 
 alpr = ALPR()
 
@@ -127,7 +125,7 @@ results = [result for result in results if len(result['lines'])]
 for result in results:
     result['label'] = '\n'.join([line.get('text', '') for line in result['lines']])
     del result['confidence']
-frame = draw.render_results(img, results)
+frame = render_results(img, results)
 show_image(img)
 ```
 
@@ -167,8 +165,7 @@ Model to predict gender and age. It can be useful to anonymize minors faces.
 
 ```python
 from abraia.faces import Recognition, Attribute
-from abraia.utils import load_image, show_image
-from abraia.draw import render_results
+from abraia.utils import load_image, show_image, render_results
 
 recognition = Recognition()
 attribute = Attribute()

abraia/__init__.py

@@ -2,7 +2,7 @@
 from dotenv import load_dotenv
 load_dotenv()
 
-__version__ = '0.20.3'
+__version__ = '0.20.4'
 
 from . import config
 from .client import Abraia, APIError

abraia/detect.py

@@ -6,8 +6,7 @@
 
 from .ops import py_cpu_nms, normalize, mask_to_polygon, softmax
 from .utils import download_file, load_json, get_color, get_providers
-from .utils import load_image, show_image, save_image, Video
-from .draw import render_results
+from .utils import load_image, show_image, save_image, Video, render_results
 
 
 def resize(img, size):

abraia/editing/__init__.py

@@ -8,7 +8,7 @@
 
 from ..detect import load_model
 from ..faces import Recognition
-from .. import draw
+from ..utils import draw
 
 
 def detect_faces(img):

abraia/utils/__init__.py

@@ -10,6 +10,7 @@
 
 from .video import Video
 from .sketcher import Sketcher
+from .draw import render_results
 
 tempdir = tempfile.gettempdir()
 
@@ -72,11 +73,6 @@ def get_color(idx):
     return colors[idx % (len(colors) - 1)]
 
 
-def hex_to_rgb(hex):
-    h = hex.lstrip('#')
-    return tuple(int(h[i:i+2], 16) for i in (0, 2, 4))
-
-
 def get_providers():
     available_providers = ort.get_available_providers()
     providers = ["CUDAExecutionProvider", "CoreMLExecutionProvider", "CPUExecutionProvider"]

abraia/draw.py → abraia/utils/draw.py

@@ -1,8 +1,10 @@
 import cv2
-import math
 import numpy as np
 
-from .utils import hex_to_rgb
+
+def hex_to_rgb(hex):
+    h = hex.lstrip('#')
+    return tuple(int(h[i:i+2], 16) for i in (0, 2, 4))
 
 
 def draw_point(img, point, color, thickness = 2):
@@ -55,19 +57,24 @@ def draw_filled_polygon(img, polygon, color, opacity = 1):
 def draw_blurred_mask(img, mask):
     w_k = int(0.1 * max(img.shape[:2]))
     w_k = w_k + 1 if w_k % 2 == 0 else w_k
-    # m_k = int(math.sqrt(w_k))
-    # m_k = m_k + 1 if m_k % 2 == 0 else m_k
-    # print(w_k, m_k)
     mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
     blurred_img = cv2.GaussianBlur(img, (w_k, w_k), 0)
-    # blurred_mask = cv2.blur(mask, (5, 5))
     img = np.where(mask==0, img, blurred_img)
     # img1 = cv2.multiply(1 - (blurred_mask / 255), img)
     # img2 = cv2.multiply(blurred_mask / 255, blurred_img)
     # img = (cv2.add(img1, img2)).astype(np.uint8)
     return img
 
 
+def draw_overlay_mask(img, mask, color = (255, 0, 0), opacity = 1):
+    img_copy = img.copy()
+    overlay = cv2.cvtColor(mask, cv2.COLOR_GRAY2RGB)
+    overlay[mask == 255] = color
+    img_over = cv2.addWeighted(img_copy, 1 - opacity, overlay, opacity, 0)
+    img_copy[mask == 255] = img_over[mask == 255]
+    return img_copy
+
+
 def draw_text(img, text, point, background_color = None, text_color = (255, 255, 255), 
               text_scale = 0.8, padding = 6):
     text_font, text_thickness = cv2.FONT_HERSHEY_DUPLEX, 1
@@ -89,9 +96,6 @@ def draw_overlay(img, overlay, rect = None, opacity = 1):
     alpha_float = (cv2.convertScaleAbs(alpha_channel * opacity).astype(np.float32) / 255)[..., np.newaxis]
     blended_roi = cv2.convertScaleAbs((1 - alpha_float) * img[y1:y2, x1:x2] + alpha_float * overlay[:, :, :3])
     img[y1:y2, x1:x2] = blended_roi
-    # img_copy = img.copy()
-    # cv2.rectangle(img_copy, pt1, pt2, color, -1)
-    # cv2.addWeighted(img_copy, opacity, img, 1 - opacity, 0, img)
     return img
 
 

abraia/utils/sketcher.py

@@ -11,14 +11,7 @@
 import cv2
 import numpy as np
 
-
-def draw_mask(img, mask, color, opacity = 1):
-    img_copy = img.copy()
-    overlay = cv2.cvtColor(mask, cv2.COLOR_GRAY2RGB)
-    overlay[mask == 255] = color
-    img_over = cv2.addWeighted(img_copy, 1 - opacity, overlay, opacity, 0)
-    img_copy[mask == 255] = img_over[mask == 255]
-    return img_copy
+from .draw import draw_overlay_mask
 
 
 class Sketcher:
@@ -42,7 +35,7 @@ def dilate(self, mask):
 
     def show(self, img, mask=None):
         if mask is not None:
-            img = draw_mask(img, mask, (255, 0, 0), 0.5)
+            img = draw_overlay_mask(img, mask, (255, 0, 0), 0.5)
         self.output = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
         cv2.imshow(self.win_name, self.output)