Merge pull request #235 from 1adrianb/devel

Fix multiple issues, restructure code partially

.travis.yml

@@ -4,6 +4,7 @@ python:
   - "3.5"
   - "3.6"
   - "3.7"
+  - "3.8"
 
 addons:
   apt_packages:
@@ -24,7 +25,7 @@ install:
   # Useful for debugging any issues with conda
   - conda info -a
 
-  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION pytorch-cpu -c pytorch
+  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION pytorch cpuonly -c pytorch
   - source activate test-environment
   - travis_retry pip install --upgrade pip setuptools wheel
   - travis_retry pip install -r requirements.txt

Dockerfile

@@ -1,4 +1,4 @@
-# Based on https://github.com/pytorch/pytorch/blob/master/Dockerfile
+# Based on a older version of https://github.com/pytorch/pytorch/blob/master/Dockerfile
 FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
 
 RUN apt-get update && apt-get install -y --no-install-recommends \

README.md

@@ -85,9 +85,9 @@ Please also see the ``examples`` folder
 
 ### Requirements
 
-* Python 3.5+ or Python 2.7 (it may work with other versions too). Support for Python 2.7 is deprecated.
+* Python 3.5+ (it may work with other versions too). Last version with support for python 2.7 was v1.1.1
 * Linux, Windows or macOS
-* pytorch (>=1.0)
+* pytorch (>=1.2)
 
 While not required, for optimal performance(especially for the detector) it is **highly** recommended to run the code using a CUDA enabled GPU.
 
@@ -104,39 +104,7 @@ Alternatively, bellow, you can find instruction to build it from source.
 
 ### From source
 
- Install pytorch and pytorch dependencies. Instructions taken from [pytorch readme](https://github.com/pytorch/pytorch). For a more updated version check the framework github page.
-
- On Linux
-```bash
-export CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" # [anaconda root directory]
-
-# Install basic dependencies
-conda install numpy pyyaml mkl setuptools cmake gcc cffi
-
-# Add LAPACK support for the GPU
-conda install -c soumith magma-cuda80 # or magma-cuda75 if CUDA 7.5
-```
-
-On OSX
-```bash
-export CMAKE_PREFIX_PATH=[anaconda root directory]
-conda install numpy pyyaml setuptools cmake cffi
-```
-#### Get the PyTorch source
-```bash
-git clone --recursive https://github.com/pytorch/pytorch
-```
-
-#### Install PyTorch
-On Linux
-```bash
-python setup.py install
-```
-
-On OSX
-```bash
-MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install
-```
+ Install pytorch and pytorch dependencies. Please check the [pytorch readme](https://github.com/pytorch/pytorch) for this.
 
 #### Get the Face Alignment source code
 ```bash
@@ -150,7 +118,7 @@ python setup.py install
 
 ### Docker image
 
-A Dockerfile is provided to build images with cuda support and cudnn v5. For more instructions about running and building a docker image check the orginal Docker documentation.
+A Dockerfile is provided to build images with cuda support and cudnn. For more instructions about running and building a docker image check the orginal Docker documentation.
 ```
 docker build -t face-alignment .
 ```
@@ -161,7 +129,7 @@ While here the work is presented as a black-box, if you want to know more about
 
 ## Contributions
 
-All contributions are welcomed. If you encounter any issue (including examples of images where it fails) feel free to open an issue.
+All contributions are welcomed. If you encounter any issue (including examples of images where it fails) feel free to open an issue. If you plan to add a new features please open an issue to discuss this prior to making a pull request.
 
 ## Citation
 
@@ -180,4 +148,4 @@ For citing dlib, pytorch or any other packages used here please check the origin
 
 * To the [pytorch](http://pytorch.org/) team for providing such an awesome deeplearning framework
 * To [my supervisor](http://www.cs.nott.ac.uk/~pszyt/) for his patience and suggestions.
-* To all other python developers that made available the rest of the packages used in this repository.
+* To all other python developers that made available the rest of the packages used in this repository.

face_alignment/__init__.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 
 __author__ = """Adrian Bulat"""
-__email__ = 'adrian[email protected]'
+__email__ = 'adrian@adrianbulat.com'
 __version__ = '1.1.1'
 
 from .api import FaceAlignment, LandmarksType, NetworkSize

face_alignment/api.py

@@ -1,16 +1,9 @@
-from __future__ import print_function
-import os
 import torch
 from torch.utils.model_zoo import load_url
 from enum import Enum
 from skimage import io
 from skimage import color
 import numpy as np
-import cv2
-try:
-    import urllib.request as request_file
-except BaseException:
-    import urllib as request_file
 
 from .models import FAN, ResNetDepth
 from .utils import *
@@ -269,15 +262,3 @@ def get_landmarks_from_directory(self, path, extensions=['.jpg', '.png'], recurs
             predictions[image_path] = preds
 
         return predictions
-
-    @staticmethod
-    def remove_models(self):
-        base_path = os.path.join(appdata_dir('face_alignment'), "data")
-        for data_model in os.listdir(base_path):
-            file_path = os.path.join(base_path, data_model)
-            try:
-                if os.path.isfile(file_path):
-                    print('Removing ' + data_model + ' ...')
-                    os.unlink(file_path)
-            except Exception as e:
-                print(e)

face_alignment/detection/blazeface/blazeface_detector.py

@@ -1,22 +1,11 @@
-import os
-import cv2
 from torch.utils.model_zoo import load_url
 
 from ..core import FaceDetector
+from ...utils import load_file_from_url
 
 from .net_blazeface import BlazeFace
 from .detect import *
 
-import requests
-import io
-
-
-def load_numpy_from_url(url):
-    response = requests.get(url)
-    response.raise_for_status()
-    data = np.load(io.BytesIO(response.content))  # Works!
-    return data
-
 models_urls = {
     'blazeface_weights': 'https://github.com/hollance/BlazeFace-PyTorch/blob/master/blazeface.pth?raw=true',
     'blazeface_anchors': 'https://github.com/hollance/BlazeFace-PyTorch/blob/master/anchors.npy?raw=true'
@@ -30,7 +19,7 @@ def __init__(self, device, path_to_detector=None, path_to_anchor=None, verbose=F
         # Initialise the face detector
         if path_to_detector is None:
             model_weights = load_url(models_urls['blazeface_weights'])
-            model_anchors = load_numpy_from_url(models_urls['blazeface_anchors'])
+            model_anchors = np.load(load_file_from_url(models_urls['blazeface_anchors']))
         else:
             model_weights = torch.load(path_to_detector)
             model_anchors = np.load(path_to_anchor)

face_alignment/detection/blazeface/detect.py

@@ -1,20 +1,10 @@
 import torch
 import torch.nn.functional as F
 
-import os
-import sys
 import cv2
-import random
-import datetime
-import math
-import argparse
 import numpy as np
 
-import scipy.io as sio
-import zipfile
-
 from .utils import *
-# from .net_blazeface import s3fd
 
 
 def detect(net, img, device):

face_alignment/detection/dlib/dlib_detector.py

@@ -1,44 +1,22 @@
-import os
+import warnings
 import cv2
 import dlib
 
-try:
-    import urllib.request as request_file
-except BaseException:
-    import urllib as request_file
-
 from ..core import FaceDetector
-from ...utils import appdata_dir
+from ...utils import load_file_from_url
 
 
 class DlibDetector(FaceDetector):
     def __init__(self, device, path_to_detector=None, verbose=False):
         super().__init__(device, verbose)
 
-        print('Warning: this detector is deprecated. Please use a different one, i.e.: S3FD.')
-        base_path = os.path.join(appdata_dir('face_alignment'), "data")
-        os.makedirs(base_path, exist_ok=True)
+        warnings.warn('Warning: this detector is deprecated. Please use a different one, i.e.: S3FD.')
 
         # Initialise the face detector
         if 'cuda' in device:
             if path_to_detector is None:
-                path_to_detector = os.path.join(
-                    base_path, "mmod_human_face_detector.dat")
-
-                if not os.path.isfile(path_to_detector):
-                    print("Downloading the face detection CNN. Please wait...")
-
-                    path_to_temp_detector = os.path.join(
-                        base_path, "mmod_human_face_detector.dat.download")
-
-                    if os.path.isfile(path_to_temp_detector):
-                        os.remove(os.path.join(path_to_temp_detector))
-
-                    request_file.urlretrieve(
-                        "https://www.adrianbulat.com/downloads/dlib/mmod_human_face_detector.dat",
-                        os.path.join(path_to_temp_detector))
-
-                    os.rename(os.path.join(path_to_temp_detector), os.path.join(path_to_detector))
+                path_to_detector = load_file_from_url(
+                    "https://www.adrianbulat.com/downloads/dlib/mmod_human_face_detector.dat")
 
             self.face_detector = dlib.cnn_face_detection_model_v1(path_to_detector)
         else:

face_alignment/detection/sfd/bbox.py

@@ -1,4 +1,3 @@
-from __future__ import print_function
 import os
 import sys
 import cv2

face_alignment/models/__init__.py

@@ -0,0 +1,2 @@
+from .fan import FAN
+from .resnet import ResNetDepth