Full RTX Support

Remove FFMPEG from Conda Requirements
Fix Tensorboard logging for Tensorflow 1.13.1
Bump default Conda Tensorflow to 1.13.1
Update max python version to 3.7

INSTALL.md

@@ -142,7 +142,7 @@ It's good to keep faceswap up to date as new features are added and bugs are fix
 
 # General Install Guide
 ## Installing dependencies
-- Python >= 3.2-3.6 64-bit (cannot be 3.7.x as Tensorflow has not been updated to provide support)
+- Python >= 3.2-3.7 64-bit
   - apt/yum install python3 (Linux)
   - [Installer](https://www.python.org/downloads/release/python-368/) (Windows)
   - [brew](https://brew.sh/) install python3 (macOS)
@@ -181,13 +181,13 @@ INFO    CUDA Enabled
 INFO    1. Install Docker
         https://www.docker.com/community-edition
         
-        2. Install Nvidia-Docker & Restart Docker Service
+        1. Install Nvidia-Docker & Restart Docker Service
         https://github.com/NVIDIA/nvidia-docker
         
-        3. Build Docker Image For Faceswap
+        1. Build Docker Image For Faceswap
         docker build -t deepfakes-gpu -f Dockerfile.gpu .
         
-        4. Mount faceswap volume and Run it
+        1. Mount faceswap volume and Run it
         # without gui. tools.py gui not working.
         nvidia-docker run --rm -it -p 8888:8888 \
             --hostname faceswap-gpu --name faceswap-gpu \
@@ -211,7 +211,7 @@ INFO    1. Install Docker
             -e UID=`id -u` \
             deepfakes-gpu
         
-        5. Open a new terminal to interact with the project
+        1. Open a new terminal to interact with the project
         docker exec faceswap-gpu python /srv/faceswap.py gui
 ```
 

plugins/train/trainer/_base.py

@@ -27,7 +27,7 @@
 import cv2
 import numpy as np
 
-from tensorflow import keras as tf_keras
+import tensorflow as tf
 
 from lib.alignments import Alignments
 from lib.faces_detect import DetectedFace
@@ -113,22 +113,33 @@ def set_tensorboard(self):
 
         logger.debug("Enabling TensorBoard Logging")
         tensorboard = dict()
+
         for side in self.sides:
             logger.debug("Setting up TensorBoard Logging. Side: %s", side)
             log_dir = os.path.join(str(self.model.model_dir),
                                    "{}_logs".format(self.model.name),
                                    side,
                                    "session_{}".format(self.model.state.session_id))
-            tbs = tf_keras.callbacks.TensorBoard(log_dir=log_dir,
-                                                 histogram_freq=0,  # Must be 0 or hangs
-                                                 batch_size=self.batch_size,
-                                                 write_graph=True,
-                                                 write_grads=True)
+            tbs = tf.keras.callbacks.TensorBoard(log_dir=log_dir, **self.tensorboard_kwargs)
             tbs.set_model(self.model.predictors[side])
             tensorboard[side] = tbs
         logger.info("Enabled TensorBoard Logging")
         return tensorboard
 
+    @property
+    def tensorboard_kwargs(self):
+        """ TF 1.13 + needs an additional kwarg which is not valid for earlier versions """
+        kwargs = dict(histogram_freq=0,  # Must be 0 or hangs
+                      batch_size=64,
+                      write_graph=True,
+                      write_grads=True)
+        tf_version = [int(ver) for ver in tf.__version__.split(".")]
+        logger.debug("Tensorflow version: %s", tf_version)
+        if tf_version[0] > 1 or (tf_version[0] == 1 and tf_version[1] > 12):
+            kwargs["update_freq"] = "batch"
+        logger.debug(kwargs)
+        return kwargs
+
     def print_loss(self, loss):
         """ Override for specific model loss formatting """
         logger.trace(loss)

scripts/convert.py

@@ -474,7 +474,7 @@ def get_trainer(self, model_dir):
                      if fname.endswith("_state.json")]
         if len(statefile) != 1:
             logger.error("There should be 1 state file in your model folder. %s were found. "
-                         "Specify a trainer with the '-t', '--trainer' option.")
+                         "Specify a trainer with the '-t', '--trainer' option.", len(statefile))
             exit(1)
         statefile = os.path.join(str(model_dir), statefile[0])
 

setup.py

@@ -21,7 +21,7 @@ class Environment():
     """ The current install environment """
     def __init__(self):
         self.macos_required_packages = ["pynvx==0.0.4"]
-        self.conda_required_packages = [("ffmpeg", "conda-forge"), ("tk", )]
+        self.conda_required_packages = [("tk", )]
         self.output = Output()
         # Flag that setup is being run by installer so steps can be skipped
         self.is_installer = False
@@ -138,10 +138,10 @@ def check_python(self):
         self.output.info("Installed Python: {0} {1}".format(self.py_version[0],
                                                             self.py_version[1]))
         if not (self.py_version[0].split(".")[0] == "3"
-                and self.py_version[0].split(".")[1] in ("3", "4", "5", "6")
+                and self.py_version[0].split(".")[1] in ("3", "4", "5", "6", "7")
                 and self.py_version[1] == "64bit"):
-            self.output.error("Please run this script with Python version 3.3, 3.4, 3.5 or 3.6 "
-                              "64bit and try again.")
+            self.output.error("Please run this script with Python version 3.3, 3.4, 3.5, 3.6 or "
+                              "3.7 64bit and try again.")
             exit(1)
 
     def output_runtime_info(self):
@@ -253,9 +253,9 @@ def update_tf_dep(self):
     def update_tf_dep_conda(self):
         """ Update Conda TF Dependency """
         if not self.enable_cuda:
-            self.required_packages.append("tensorflow==1.12.0")
+            self.required_packages.append("tensorflow==1.13.1")
         else:
-            self.required_packages.append("tensorflow-gpu==1.12.0")
+            self.required_packages.append("tensorflow-gpu==1.13.1")
 
 
 class Output():