                      "GPUs."
                      "\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"
                      "\nL|'fan-amd': Face Alignment Network. Uses Keras backend to support AMD "
                      "Cards. Best aligner. GPU heavy, slow when not running on GPU"})
          argument_list.append({"opts": ("-nm", "--normalization"),
                                "action": Radio,
                                "type": str.lower,
                                "dest": "normalization",
                                "choices": ["none", "clahe", "hist", "mean"],
 
</s> remove             "default": "fan",
            "help": "R|Aligner to use. NB: Unless stated, all aligners will run on CPU for AMD "
                    "GPUs."
 </s> add             "default": default_aligner,
            "help": "R|Aligner to use." </s> remove                     "detectors but can often return more false positives."
                    "\nL|'s3fd': Fast on GPU, slow on CPU. Can detect more faces and fewer false "
                    "positives than other GPU detectors, but is a lot more resource intensive."})
 </s> add                     "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 "
                    "fewer false positives than other GPU detectors, but is a lot more resource "
                    "intensive."}) </s> remove                                       "then alignment (2 passes). Useful if VRAM is at a premium. "
                                      "Only has an effect if both the aligner and detector use "
                                      "the GPU, otherwise this is automatically off. NB: AMD "
                                      "cards do not support parallel processing, so if both "
                                      "aligner and detector use an AMD GPU this will "
                                      "automatically be enabled."})
 </s> add                                       "then alignment (2 passes). Useful if VRAM is at a "
                                      "premium."})
                    "\nL|'" + fan + "': Face Alignment Network. Best aligner. GPU "
                    "heavy, slow when not running on GPU"})
                      "GPUs."
                      "\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"})
                    "\nL|'" + fan + "': Face Alignment Network. Best aligner. GPU "
                    "heavy, slow when not running on GPU"})
                    "\nL|'" + fan + "': Face Alignment Network. Best aligner. GPU "
                    "heavy, slow when not running on GPU"})
                    "\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",
                                "choices": ["none", "clahe", "hist", "mean"],
keep keep keep keep replace replace replace replace keep keep keep keep keep
 More seamless AMD Integration

- utils.py: Set FS backend if .faceswap config file doesn't exist
- setup.py: set .faceswap config on setup
- Dynamically load options for AMD/CPU/NVIDIA backends 
lib/cli.py