didn't find a face

• face_recognition version: 1.2.3
• Python version: 3.5
• Operating System: Ubuntu 16.04

Description

I had been using your virtual machine ... Thank you BTW. Then I modified one of your scripts ever so slightly so that I could separate the training and the recognition. Everything worked wonderfully except the performance. I then purchased a machine with 5 GPUs. I installed Ubuntu 16.04 and tensorflow-gpu. Now when I train I get the following...

train_dir = knn_examples/train
Traceback (most recent call last):
File "train.py", line 86, in
knn_clf = train("knn_examples/train")
File "train.py", line 22, in train
faces_bboxes = face_locations(image)
File "/home/rwilson/.local/lib/python3.5/site-packages/face_recognition/api.py", line 77, in face_locations
return [_rect_to_css(face) for face in _raw_face_locations(img, number_of_times_to_upsample)]
File "/home/rwilson/.local/lib/python3.5/site-packages/face_recognition/api.py", line 66, in _raw_face_locations
return face_detector(img, number_of_times_to_upsample)
RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

Since everything is Identical I assume that something is wrong with my setup. Maybe a wrong version of something.

pip3 freeze
apturl==0.5.2
beautifulsoup4==4.4.1
blinker==1.3
Brlapi==0.6.4
chardet==2.3.0
checkbox-support==0.22
Click==7.0
cloudpickle==0.6.0
command-not-found==0.3
cryptography==1.2.3
cycler==0.10.0
dask==0.19.3
decorator==4.3.0
defer==1.0.6
dlib==19.16.0
face-recognition==1.2.3
face-recognition-models==0.3.0
feedparser==5.1.3
guacamole==0.9.2
html5lib==0.999
httplib2==0.9.1
idna==2.0
Jinja2==2.8
kiwisolver==1.0.1
language-selector==0.1
louis==2.6.4
lxml==3.5.0
Mako==1.0.3
MarkupSafe==0.23
matplotlib==3.0.0
networkx==2.2
numpy==1.15.2
oauthlib==1.0.3
onboard==1.2.0
padme==1.1.1
pexpect==4.0.1
Pillow==5.3.0
plainbox==0.25
ptyprocess==0.5
pyasn1==0.1.9
pycups==1.9.73
pycurl==7.43.0
pygobject==3.20.0
PyJWT==1.3.0
pyparsing==2.2.2
python-apt==1.1.0b1+ubuntu0.16.4.2
python-dateutil==2.7.3
python-debian==0.1.27
python-systemd==231
PyWavelets==1.0.1
pyxdg==0.25
reportlab==3.3.0
requests==2.9.1
scikit-image==0.14.1
scikit-learn==0.20.0
scipy==1.1.0
screen-resolution-extra==0.0.0
sessioninstaller==0.0.0
six==1.11.0
sklearn==0.0
ssh-import-id==5.5
system-service==0.3
toolz==0.9.0
ubuntu-drivers-common==0.0.0
ufw==0.35
unattended-upgrades==0.1
unity-scope-calculator==0.1
unity-scope-chromiumbookmarks==0.1
unity-scope-colourlovers==0.1
unity-scope-devhelp==0.1
unity-scope-firefoxbookmarks==0.1
unity-scope-gdrive==0.7
unity-scope-manpages==0.1
unity-scope-openclipart==0.1
unity-scope-texdoc==0.1
unity-scope-tomboy==0.1
unity-scope-virtualbox==0.1
unity-scope-yelp==0.1
unity-scope-zotero==0.1
urllib3==1.13.1
usb-creator==0.3.0
xdiagnose==3.8.4.1
xkit==0.0.0
XlsxWriter==0.7.3

What I Did

Paste the command(s) you ran and the output.
If there was a crash, please include the traceback here.

Start with train.py line 22 and face_recognition/api.py lines 66-77, using the supplied traceback and package versions to reproduce the failure. Check the image input and environment details involved in face_locations; done means identifying a reproducible cause and documenting or validating a fix for the unsupported image type.