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face_recognition
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changes for windows compatibility

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testqueue
Ruben van de Ven 2 years ago
parent e21376465f
commit a7ea09fb52
3 changed files with 87 additions and 57 deletions
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  1. 139
      face_recognition/comparison.py
  2. 3
      requirements.txt
  3. 2
      visualhaar

139
face_recognition/comparison.py
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@ -10,12 +10,21 @@ from PIL import ImageFont, ImageDraw, Image
import os
draw_colors = {
'hog': (255,0,0),
'haar': (0,255,0),
'dnn': (0,0,255),
'hog': (198,65,124),
'haar': (255,255,255),
'dnn': (251,212,36),
}
font = ImageFont.truetype("/home/ruben/Documents/Projecten/2018/PATH/presentation/lib/font/source-sans-pro/source-sans-pro-regular.ttf", 30)
titles = {
'hog' : "Histogram of oriented gradients",
'haar' : "Haar cascades",
'dnn' : "Neural network",
}
fontfile = "SourceSansPro-Regular.ttf"
font = ImageFont.truetype(fontfile, 30)
font_s = ImageFont.truetype(fontfile, 20)
class Result():
def __init__(self, algorithm, image, confidence_threshold = 0.5):
@ -34,13 +43,17 @@ class Result():
})
return self
def draw_detections(self):
def draw_detections(self, include_title = False):
cv2_im_rgb = cv2.cvtColor(self.visualisation,cv2.COLOR_BGR2RGB)
# Pass the image to PIL
pil_im = Image.fromarray(cv2_im_rgb)
draw = ImageDraw.Draw(pil_im, 'RGBA')
self.draw_detections_on(draw)
if include_title:
draw.text((10,10), titles[self.algorithm], fill=draw_colors[self.algorithm], font=font)
return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def draw_detections_on(self, draw: ImageDraw):
@ -94,6 +107,9 @@ class Result():
)
return result
def count_detections(self):
detections = [d for d in self.detections if d['confidence'] > self.confidence_threshold]
return len(detections)
def record(device_id, q1,q2, q3, q4, resolution, rotate):
@ -324,7 +340,17 @@ def process3_haar(in_q, out_q, cascade_file):
""")
dir_path = os.path.dirname(os.path.realpath(__file__))
C = ffi.dlopen(os.path.join(dir_path,"../visualhaar/target/debug/libvisual_haarcascades_lib.so"))
lib_path = os.path.join(dir_path, "..", "visualhaar", "target", "debug")
so_path = os.path.join(lib_path, "libvisual_haarcascades_lib.so")
dll_path = os.path.join(lib_path, "visual_haarcascades_lib.dll")
if os.path.exists(so_path):
C = ffi.dlopen(so_path)
elif os.path.exists(dll_path):
C = ffi.dlopen(dll_path)
else:
raise RuntimeException("Visual haarcascades library is not found")
# print(C.test(9))
# i = Image.open("Marjo.jpg")
@ -400,62 +426,65 @@ def process3_haar(in_q, out_q, cascade_file):
# print(img)
out_q.put(result)
def draw_stats(image, results):
pil_im = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
draw = ImageDraw.Draw(pil_im, 'RGBA')
for i, result in enumerate(results):
if result is None:
continue
c = result.count_detections()
txt = "face" if c == 1 else "faces"
txt = f"{result.algorithm.ljust(5)} {c} {txt}"
draw.text((10, pil_im.size[1] - i*25 - 50), txt, fill=draw_colors[result.algorithm], font=font_s, stroke_width=1, stroke_fill=(0,0,0))
return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
logger = logging.getLogger('display')
empty_image = np.zeros((image_res[1],image_res[0],3), np.uint8)
prev_image1 = None
prev_result2 = None
prev_result3 = None
prev_result4 = None
if fullscreen:
cv2.namedWindow("output", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("output",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
results = [None, None, None]
result_queues = [q2, q3, q4]
images = [empty_image, empty_image, empty_image, empty_image]
override_image = None
override_until = None
if fullscreen:
cv2.namedWindow("output", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("output",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
while True:
logging.debug('r')
try:
image1 = q1.get_nowait()
image1 = cv2.resize(image1, (image_res[0], image_res[1]))
prev_image1 = image1
image = q1.get_nowait()
images[0] = cv2.resize(image, (image_res[0], image_res[1]))
except Empty as e:
image1 = prev_image1 if prev_image1 is not None else empty_image
try:
result2 = q2.get_nowait()
result2 = result2.resize(image_res[0], image_res[1])
prev_result2 = result2
except Empty as e:
result2 = prev_result2
finally:
image2 = result2.draw_detections() if result2 is not None else empty_image
try:
result3 = q3.get_nowait()
result3 = result3.resize(image_res[0], image_res[1])
prev_result3 = result3
except Empty as e:
result3 = prev_result3
finally:
image3 = result3.draw_detections() if result3 is not None else empty_image
try:
result4 = q4.get_nowait()
result4 = result4.resize(image_res[0], image_res[1])
prev_result4 = result4
except Empty as e:
result4 = prev_result4
finally:
image4 = result4.draw_detections() if result4 is not None else empty_image
pass
for idx, queue in enumerate(result_queues):
try:
result = queue.get_nowait()
results[idx] = result.resize(image_res[0], image_res[1])
images[idx+1] = results[idx].draw_detections(include_title=True)
except Empty as e:
pass
finally:
pass
if override_image is not None and override_until > time.time():
cv2.imshow("output", override_image)
else:
override_image = None
img_concate_Verti1 = np.concatenate((image1,image2),axis=0)
img_concate_Verti2 = np.concatenate((image3,image4),axis=0)
images[0] = draw_stats(images[0], results)
img_concate_Verti1 = np.concatenate((images[0],images[1]),axis=0)
img_concate_Verti2 = np.concatenate((images[2],images[3]),axis=0)
grid_img = np.concatenate((img_concate_Verti1,img_concate_Verti2),axis=1)
cv2.imshow("output", grid_img)
@ -466,18 +495,16 @@ def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
if key == ord(' '):
# TODO wait for frame to be processed. Eg. if I move and make a pic, it should use the last frame...
output_res = (image_res[0] *2, image_res[1] * 2)
pil_im = Image.fromarray(cv2.cvtColor(image1, cv2.COLOR_BGR2RGB))
pil_im = Image.fromarray(cv2.cvtColor(images[0], cv2.COLOR_BGR2RGB))
pil_im = pil_im.resize(output_res)
draw = ImageDraw.Draw(pil_im, 'RGBA')
if result2 is not None:
result2.resize(output_res[0], output_res[1]).draw_detections_on(draw)
if result3 is not None:
result3.resize(output_res[0], output_res[1]).draw_detections_on(draw)
if result4 is not None:
result4.resize(output_res[0], output_res[1]).draw_detections_on(draw)
for result in results:
if result is None:
continue
result.resize(output_res[0], output_res[1]).draw_detections_on(draw)
override_image = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
override_until = time.time() + 5
logger.info("Show frame until %f", override_until)
@ -485,9 +512,9 @@ def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
# save images:
name = datetime.datetime.now().isoformat(timespec='seconds')
cv2.imwrite(os.path.join(output_dir, f'{name}.png'),override_image)
cv2.imwrite(os.path.join(output_dir, f'{name}-hog.png'),result2.visualisation)
cv2.imwrite(os.path.join(output_dir, f'{name}-dnn.png'),result3.visualisation)
cv2.imwrite(os.path.join(output_dir, f'{name}-haar.png'),result4.visualisation)
for result in results:
cv2.imwrite(os.path.join(output_dir, f'{name}-{result.algorithm}.png'),result.visualisation)
def main(camera_id, rotate, fullscreen, cascade_file, output_dir):
image_size = (int(1920/2), int(1080/2))

3
requirements.txt
Unescape View File

@ -2,3 +2,6 @@ scipy
numpy
dlib
Pillow
opencv-python
cffi
scikit-image

2
visualhaar

@ -1 +1 @@
Subproject commit 7de5440484842c147944ae123fa689333846dde7
Subproject commit 928da82d24de1ae2cef268c140f9992b0614806b
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