              "help": "R|Aligner to use."
                      "\nL|'cv2-dnn': A cpu only CNN based landmark detector. Faster, less "
                      "resource intensive, but less accurate. Only use this if not using a gpu "
                      " and time is important."
                      "\nL|'" + fan + "': Face Alignment Network. Best aligner. GPU "
                      "heavy, slow when not running on GPU"})
          argument_list.append({"opts": ("-nm", "--normalization"),
                                "action": Radio,
                                "type": str.lower,
                                "dest": "normalization",
 
</s> remove                     "\nL|'cv2-dnn': A cpu only CNN based landmark detector. Faster, less "
 </s> add                     "\nL|cv2-dnn: A cpu only CNN based landmark detector. Faster, less " </s> remove                     "\nL|'mtcnn': Fast on GPU, slow on CPU. Uses fewer resources than other GPU "
                    "detectors but can often return more false positives. NB: Runs on CPU for AMD "
                    "cards."
                    "\nL|'" + s3fd + "': Fast on GPU, slow on CPU. Can detect more faces and "
 </s> add                     "\nL|mtcnn: Fast on GPU, slow on CPU. Uses fewer resources than other GPU "
                    "detectors but can often return more false positives."
                    "\nL|s3fd: Fast on GPU, slow on CPU. Can detect more faces and " </s> remove                     "\nL|'cv2-dnn': A CPU only extractor, is the least reliable, but uses least "
 </s> add                     "\nL|cv2-dnn: A CPU only extractor, is the least reliable, but uses least " </s> remove         s3fd = "s3fd"
        fan = "fan"
        if backend == "cpu":
            default_detector = default_aligner = "cv2-dnn"
        else:
            default_detector = s3fd
            default_aligner = fan
        if backend == "amd":
            default_detector += "-amd"
            default_aligner += "-amd"
            s3fd += "-amd"
            fan += "-amd"

 </s> add  </s> remove                                       "\nL|'none': Don't perform normalization on the face."
                                      "\nL|'clahe': Perform Contrast Limited Adaptive Histogram "
 </s> add                                       "\nL|none: Don't perform normalization on the face."
                                      "\nL|clahe: Perform Contrast Limited Adaptive Histogram "
                    "\nL|fan: Face Alignment Network. Best aligner. GPU "
              "help": "R|Aligner to use."
                      "\nL|'cv2-dnn': A cpu only CNN based landmark detector. Faster, less "
                      "resource intensive, but less accurate. Only use this if not using a gpu "
                      " and time is important."
                    "\nL|fan: Face Alignment Network. Best aligner. GPU "
                      "heavy, slow when not running on GPU"})
          argument_list.append({"opts": ("-nm", "--normalization"),
                                "action": Radio,
                                "type": str.lower,
                                "dest": "normalization",
keep keep keep keep replace keep keep keep keep keep
 De-Multiprocess Extract (#871)

* requirements.txt: - Pin opencv to 4.1.1 (fixes cv2-dnn error)

* lib.face_detect.DetectedFace: change LandmarksXY to landmarks_xy. Add left, right, top, bottom attributes

* lib.model.session: Session manager for loading models into different graphs (for Nvidia + CPU)

* plugins.extract._base: New parent class for all extract plugins

* plugins.extract.pipeline. Remove MultiProcessing. Dynamically limit batchsize for Nvidia cards. Remove loglevel input

* S3FD + FAN plugins. Standardise to Keras version for all backends

* Standardize all extract plugins to new threaded codebase

* Documentation. Start implementing Numpy style docstrings for Sphinx Documentation

* Remove s3fd_amd. Change convert OTF to expect DetectedFace object

* faces_detect - clean up and documentation

* Remove PoolProcess

* Migrate manual tool to new extract workflow

* Remove AMD specific extractor code from cli and plugins

* Sort tool to new extract workflow

* Remove multiprocessing from project

* Remove multiprocessing queues from QueueManager

* Remove multiprocessing support from logger

* Move face_filter to new extraction pipeline

* Alignments landmarksXY > landmarks_xy and legacy handling

* Intercept get_backend for sphinx doc build

# Add Sphinx documentation 
lib/cli.py