Changes after feedback + better Windows installer explanation in Readme

master
Ruben van de Ven 2 years ago
parent b3b407a99e
commit 12ce9e1751
  1. 2
      .vscode/launch.json
  2. 22
      README.md
  3. 51
      face_recognition/comparison.py
  4. 2
      visualhaar

@ -17,7 +17,7 @@
"request": "launch",
"program": "mirror.py",
"args": [
// "--windowed",
"--windowed",
"--output", "/tmp/face_saves",
"--camera", "0",
],

@ -12,18 +12,22 @@ A `mirror` which shows which faces are detected through three different facial d
The installation in Windows can be done, though it is quite elaborate:
* Install python3
* Install VS C++
* Install VS C++ build tools
* Install Cmake (needed for python dlib)
+ make sure to add it to path
* Install git
+ including ssh deploy key
* `git clone https://git.rubenvandeven.com/r/face_detector`
* `git clone https://git.rubenvandeven.com/r/face_recognition`
* `cd face_recognition`
* `pip install virtualenv`
* `virtualenv.exe venv`
+ Might be that you need to run: `C:\Users\DP Medialab\AppData\Roaming\Python\Python39\Scripts\virtualenv.exe` (see pip output)
* `.\venv\Scripts\activate`
+ Might be that you need to first run `Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser`
* `cd .\dnn\face_detector`
* `python.exe .\download_weights.py`
* `cd ..\..`
* `pip.exe install -r requirements.txt`
* `cd .\visualhaar`
* Either one of:
+ Compile rust library
@ -35,4 +39,16 @@ The installation in Windows can be done, though it is quite elaborate:
+ Make the installer:
* `& 'C:\Users\DP Medialab\AppData\Roaming\Python\Python38\Scripts\pyinstaller.exe' .\mirror.py --add-binary '.\visualhaar\target\release\visual_haarcascades_lib.dll;.' --add-data '.\haarcascade_frontalface_alt2.xml;.' --add-data '.\SourceSansPro-Regular.ttf;.' --add-data 'dnn;dnn'`
* `mv '.\dist\mirror\mpl-data' '.\dist\mirror\matplotlib\'`
* `Compress-Archive -LiteralPath .\dist\mirror -DestinationPath .\dist\mirror.zip`
+ We could also [use wine for cross compilation](https://www.andreafortuna.org/2017/12/27/how-to-cross-compile-a-python-script-into-a-windows-executable-on-linux/) from Linux
- make sure wine is set to pose as Windows 10 (`winecfg`)
- `wine ~/Downloads/python-3.9.0-amd64.exe` (or whichever version you use)
- Install for all users
-
## Instructor help
If screen stays black: is the camera on?
Enable camera through keyboard (MSI laptops: fn+F6). Then go to Settings/Instellingen -> Privacy instellingen voor camera -> Grant apps access to camera.

@ -9,6 +9,7 @@ import math
import datetime
from PIL import ImageFont, ImageDraw, Image
import os
import sys
draw_colors = {
'hog': (198,65,124),
@ -62,22 +63,22 @@ class Result():
return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def draw_detections_on(self, draw: ImageDraw, coloured=False):
def draw_detections_on(self, draw: ImageDraw, coloured=False, onlyIfConfident=False):
'''
Draw on a specified canvas
'''
color = draw_colors[self.algorithm] if coloured else (255,255,255)
for detection in self.detections:
self.draw_detection(draw, detection, color)
self.draw_detection(draw, detection, color, onlyIfConfident)
def draw_detection(self, draw: ImageDraw, detection: dict, color: tuple):
def draw_detection(self, draw: ImageDraw, detection: dict, color: tuple, onlyIfConfident: bool = False):
if detection['confidence'] > self.confidence_threshold:
width = 8
# draw the bounding box of the face along with the associated
# probability
text = "{:.2f}%".format(detection['confidence'] * 100)
text = "{:.0f}%".format(detection['confidence'] * 100)
y = detection['startY'] - 40 if detection['startY'] - 40 > 10 else detection['startY'] + 10
draw.text((detection['startX'], y), text, font=font, fill=color, stroke_fill=(0,0,0,100), stroke_width=1)
@ -87,6 +88,9 @@ class Result():
alpha = 1
draw.rectangle((detection['startX']-1, detection['startY']-1, detection['endX']+1, detection['endY']+1), outline=(0,0,0,100), width=1)
draw.rectangle((detection['startX']+width, detection['startY']+width, detection['endX']-width, detection['endY']-width), outline=(0,0,0,100), width=1)
elif onlyIfConfident:
# Only draw if above threshold, so this should be ignored.
return
else:
width = int(detection['confidence'] * 10 * 8)
# At least 10% opacity
@ -148,7 +152,7 @@ def record(device_id, q1,q2, q3, q4, resolution, rotate):
ret, image = capture.read()
if image is None:
logging.critical("Error with camera?")
exit()
sys.exit()
if rotate is not None:
@ -434,7 +438,7 @@ def process3_haar(in_q, out_q, cascade_file, library_filename = None):
start = time.time()
C.scan_image(haar, width, height, buffer2, buffer, buffer_len, 5, False)
logger.info(f"Visualised scan into buffer: {buffer}")
print(f"duration: {time.time() - start}s")
# print(f"duration: {time.time() - start}s")
img = Image.frombuffer(pixel_format, (width, height), ffi.buffer(buffer),
"raw", pixel_format, 0, 1)
@ -462,13 +466,13 @@ def process3_haar(in_q, out_q, cascade_file, library_filename = None):
# print(img)
out_q.put(result)
def draw_stats(image, results, padding, coloured=False):
def draw_stats(image, results, padding, coloured=False, drawDetections=False):
pil_im = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
draw = ImageDraw.Draw(pil_im, 'RGBA')
draw_stats_on_canvas(draw, results, padding, coloured)
draw_stats_on_canvas(draw, results, padding, coloured, drawDetections)
return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def draw_stats_on_canvas(draw, results, padding, coloured=False):
def draw_stats_on_canvas(draw, results, padding, coloured=False, drawDetections=False):
for i, result in enumerate(results):
if result is None:
continue
@ -478,8 +482,10 @@ def draw_stats_on_canvas(draw, results, padding, coloured=False):
txt = f"{result.algorithm.ljust(5)} {c} {txt}"
height = padding + 25
colour = draw_colors[result.algorithm] if coloured else (255,255,255)
draw.text((padding, draw.im.size[1] - i*height - height), txt, fill=colour, font=font_s, stroke_width=1, stroke_fill=(0,0,0))
draw.text((padding, draw.im.size[1] - (i+1)*height - padding), txt, fill=colour, font=font, stroke_width=2, stroke_fill=(0,0,0))
if drawDetections:
result.draw_detections_on(draw, coloured, onlyIfConfident=True)
def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
@ -566,7 +572,9 @@ def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
grid_img.shape[1] - padding - preview_width:grid_img.shape[1] - padding] = cv2.resize(image, (preview_width, preview_height), cv2.INTER_CUBIC)
# statistics
grid_img = draw_stats(grid_img, results, padding)
# for the plain webcam image (no viz), draw all detected faces.
drawDetections = (selectPreview.imageIdx == 0)
grid_img = draw_stats(grid_img, results, padding, coloured=True, drawDetections=drawDetections)
pil_im = Image.fromarray(cv2.cvtColor(grid_img, cv2.COLOR_BGR2RGB))
draw = ImageDraw.Draw(pil_im, 'RGBA')
@ -585,19 +593,30 @@ def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
# Hit 'q' on the keyboard to quit!
key = cv2.waitKey(1) & 0xFF
if key == ord('q'):
if key == ord('q') or key == 27: # key 27: escape
break
if key == ord(' ') and not override_image:
# TODO: the truth value of an array with ore than one element is ambiguous, use a.any or a.all() (OF DUS override_image is None)
if key == ord(' ') and override_image is None:
countdown_until = time.time() + 3 # seconds of countdown
# SNAP! SAVE FRAMES
if countdown_until is not None and time.time() > countdown_until:
countdown_until = None
# TODO wait for frame to be processed. Eg. if I move and make a pic, it should use the last frame...
# SNAP!
# output_res = (image_res[0] *2, image_res[1] * 2)
output_res = image_res # no scaling needed anyore
pil_im = Image.fromarray(cv2.cvtColor(cv2.flip(images[0],1), cv2.COLOR_BGR2RGB))
pil_im = pil_im.resize(output_res)
# base name for all images
name = datetime.datetime.now().isoformat(timespec='seconds').replace(':','-')
# filename of clean frame
filename = os.path.join(output_dir, f'{name}-frame.jpg')
pil_im.save(filename)
# now draw all results to the main image
draw = ImageDraw.Draw(pil_im, 'RGBA')
for result in results:
@ -613,13 +632,13 @@ def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
logger.info("Show frame until %f", override_until)
# save images:
name = datetime.datetime.now().isoformat(timespec='seconds').replace(':','-')
filename = os.path.join(output_dir, f'{name}.png')
filename = os.path.join(output_dir, f'{name}-all.png')
print(f"Save to {filename}")
r=cv2.imwrite(filename, override_image)
if not r:
raise RuntimeError(f"Could not save image {filename}")
# finally, store each visualisation with the results
for result in results:
result_img =result.draw_detections(include_title = True)
filename = os.path.join(output_dir, f'{name}-{result.algorithm}.png')

@ -1 +1 @@
Subproject commit a6ac50c3b3b7ba43cc4c18e40e9f004f01027328
Subproject commit 1319e644b1f59debe46be866d18209d2a6089e1b
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