def __init__(self, configJson, basePath=""):
minJson = os.path.join(
basePath,
configJson["minJson"]) if "minJson" in configJson else None
maxJson = os.path.join(
basePath,
configJson["maxJson"]) if "maxJson" in configJson else None
self._baseFace = VamFace(
os.path.join(basePath, configJson["baseJson"]), minJson, maxJson)
self._baseFace.trimToAnimatable()
self._paramShape = None
angles = set()
self._input_params = []
if "inputs" in configJson:
inputs = configJson["inputs"]
for param in inputs:
try:
paramName = param["name"]
paramList = []
for paramParam in param["params"]:
paramList.append({
"name": paramParam["name"],
"value": paramParam["value"]
})
if paramParam["name"] == "angle":
angles.add(float(paramParam["value"]))
self._input_params.append({
"name": paramName,
"params": paramList
})
except:
print("Error parsing parameter")
self._output_params = []
if "outputs" in configJson:
outputs = configJson["outputs"]
for param in outputs:
try:
paramName = param["name"]
paramList = []
for paramParam in param["params"]:
paramList.append({
"name": paramParam["name"],
"value": paramParam["value"]
})
if paramParam["name"] == "angle":
angles.add(float(paramParam["value"]))
self._output_params.append({
"name": paramName,
"params": paramList
})
except:
print("Error parsing parameter")
self._angles = list(angles)
self._angles.sort()
def __init__(self, paramConfig, requiredAngles, relatedFiles, baseFace):
self._config = paramConfig
self._encodings = []
self._vamFaces = []
self._angles = requiredAngles
self._angles.sort()
self._facebuckets = {}
self._baseFace = baseFace
self._generators = {
"encoding": self._encodingParams,
"json": self._jsonParams,
"eye_mouth_ratio": self._eye_mouth_ratio_params,
"mouth_chin_ratio": self._mouth_chin_ratio_params,
"eye_height_width_ratio": self._eye_height_width_ratio_params,
"nose_height_width_ratio": self._nose_height_width_ratio_params,
"brow_height_width_ratio": self._brow_height_width_ratio_params,
"brow_chin_ratio": self._brow_chin_ratio_params,
"custom_action": self._custom_action
}
for angle in self._angles:
self._facebuckets[angle] = []
# Read all encodings in from the file list
for file in relatedFiles:
try:
if isinstance(file, EncodedFace):
newFace = file
else:
newFace = EncodedFace.createFromFile(file)
self._encodings.append(newFace)
except:
try:
vamFace = VamFace(file)
vamFace.matchMorphs(baseFace)
self._vamFaces.append(vamFace)
except:
continue
# Now put the encodings into the bucket with the closest angle
for encoding in self._encodings:
nearestBucket = abs(self._angles[0])
for angle in self._angles:
if abs(abs(encoding.getAngle()) - abs(angle)) < abs(
abs(encoding.getAngle()) - abs(nearestBucket)):
nearestBucket = abs(angle)
self._facebuckets[nearestBucket].append(encoding)
def main( args ):
if args.pydev:
print("Enabling debugging with pydev")
import pydevd
pydevd.settrace(suspend=False)
templateFace = VamFace( args.templateJson )
invertTemplate = args.invertTemplate
templateFace.trimToAnimatable()
fromFace = VamFace( args.fromJson, discardExtra = False )
fileFilter = args.filter
inputDir = args.toJsonDir
outputDir = args.outputJsonDir
for root, subdirs, files in os.walk(inputDir):
print("Entering directory {}".format(root))
for file in fnmatch.filter(files, fileFilter):
try:
toName = os.path.splitext(file)[0]
outDir = root.lstrip(inputDir)
outDir = outDir.lstrip('/')
outDir = outDir.lstrip('\\')
outDir = os.path.join( outputDir, outDir )
outName = "{}_mergedWith_{}.json".format( os.path.splitext(file)[0], os.path.splitext(os.path.basename(args.fromJson))[0])
toFace = VamFace( os.path.join(root, file), discardExtra = False )
newFace = VamFace.mergeFaces( templateFace=templateFace, toFace=toFace, fromFace=fromFace, invertTemplate = invertTemplate, copyNonMorphs = True)
try:
os.makedirs(outDir)
except:
pass
outputName = os.path.join(outDir, outName )
newFace.save( outputName )
print( "Generated {}".format(outputName ) )
except Exception as e:
print("Error merging {} - {}".format(file, str(e)))
def main(args):
if args.pydev:
print("Enabling debugging with pydev")
import pydevd
pydevd.settrace(suspend=False)
inputPath = args.inputPath
outputName = args.outputName
face = None
encoding = None
for root, subdirs, files in os.walk(inputPath):
outCsvFile = os.path.join(root, outputName)
outFile = None
print("Entering {}".format(root))
for file in fnmatch.filter(files, '*.json'):
# Check if we have all support encodings for this json
basename = os.path.splitext(file)[0]
encodingFiles = [
"{}_angle0.encoding".format(basename),
"{}_angle35.encoding".format(basename)
]
hasAllFiles = True
for idx, encodingFile in enumerate(encodingFiles):
encodingFile = os.path.join(root, encodingFile)
encodingFiles[idx] = encodingFile
if not os.path.exists(encodingFile):
hasAllFiles = False
break
if not hasAllFiles:
print("Skipping {} since it does not have all encoding files".
format(file))
continue
# Have all encodings? Read them in
outArray = []
for encodingFile in encodingFiles:
encoding = open(encodingFile).read().splitlines()
outArray.extend(encoding)
face = VamFace(os.path.join(root, file))
outArray.extend(face.morphFloats)
if outFile is None:
print("Creating {}".format(outCsvFile))
outFile = open(outCsvFile, 'w')
writer = csv.writer(outFile, lineterminator='\n')
writer.writerow(outArray)
if not args.recursive:
# Don't go any further down if not recursive!
break
def main(args):
if args.pydev:
print("Enabling debugging with pydev")
import pydevd
pydevd.settrace(suspend=False)
# Delay heavy imports
from keras.models import load_model
# Work around low-memory GPU issue
import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
session = tf.Session(config=config)
modelFile = args.modelFile
inputGlob = args.inputEncoding
outputDir = args.outputDir
baseJson = args.baseJson
archiveDir = args.archiveDir
face = VamFace(baseJson)
face.trimToAnimatable()
model = load_model(modelFile)
modelName = os.path.splitext(os.path.basename(modelFile))[0]
if archiveDir:
try:
os.makedirs(archiveDir)
except:
pass
for entry in glob.glob(inputGlob):
try:
encodingFile = "{}_angle0.encoding".format(
os.path.splitext(entry)[0])
encodingFile1 = "{}_angle35.encoding".format(
os.path.splitext(entry)[0])
outArray = []
if os.path.exists(encodingFile) and os.path.exists(encodingFile1):
with open(encodingFile) as f:
encoding = f.read().splitlines()
outArray = encoding
with open(encodingFile1) as f:
encoding = f.read().splitlines()
outArray.extend(encoding)
else:
print("Missing encoding file {} or {}".format(
encodingFile, encodingFile1))
dataSet = numpy.array([outArray])
predictions = model.predict(dataSet)
rounded = [float(round(x, 5)) for x in predictions[0]]
face.importFloatList(rounded)
entryName = os.path.splitext(os.path.basename(entry))[0]
outputFile = "{}_{}.json".format(entryName, modelName)
outputFile = os.path.join(outputDir, outputFile)
if args.archiveDir and os.path.exists(outputFile):
dateString = datetime.datetime.now().strftime(
"%Y-%m-%d_%H_%M_%S")
backupFileName = os.path.splitext(
os.path.basename(outputFile))[0]
backupFileName = os.path.join(
args.archiveDir,
"{}_{}.json".format(backupFileName, dateString))
print("Backing up {} to {}".format(outputFile, backupFileName))
shutil.copyfile(outputFile, backupFileName)
face.save(outputFile)
print("Prediction saved to {}".format(outputFile))
except Exception as e:
print("Failed to process {}: {}".format(entry, e))
def main( args ):
global testJsonPath
global outputPath
if args.pydev:
print("Enabling debugging with pydev")
import pydevd
pydevd.settrace(suspend=False)
inputPath = args.inputJsonPath
#outputPath = args.outputPath
outputPath = "-"
testJsonPath = args.testJsonPath
numThreads = args.numThreads
recursive = args.recursive
fileFilter = args.filter
print( "Input path: {}\nOutput path: {}\n\n".format( inputPath, outputPath ) )
# Initialize the Vam window
vamWindow = VamWindow()
# Locating the buttons via image comparison does not reliably work. These coordinates are the 'Window' coordinates
# found via AutoHotKey's Window Spy, cooresponding to the Load Preset button and the location of the test file
vamWindow.setClickLocations([(130,39), (248,178)])
print("Initializing worker processes...")
poolWorkQueue = multiprocessing.Queue(maxsize=200)
doneEvent = multiprocessing.Event()
if numThreads > 1:
pool = []
for idx in range(numThreads):
proc = multiprocessing.Process(target=worker_process_func, args=(idx, poolWorkQueue, doneEvent) )
proc.start()
pool.append( proc )
else:
pool = None
doneEvent.set()
angles = [0, 35, 65]
for root, subdirs, files in os.walk(inputPath):
print("Entering directory {}".format(root))
for file in fnmatch.filter(files, fileFilter):
print("Processing {}".format(file))
try:
alreadyDone = False
for angle in angles:
fileName = "{}_angle{}.png".format( os.path.splitext(file)[0], angle)
fileName = os.path.join( root,fileName)
if os.path.exists(fileName):
alreadyDone = True
print("Output file already exists. Skipping.")
break
if alreadyDone:
continue
if (GetKeyState(VK_CAPITAL) or GetKeyState(VK_SCROLL)):
print("WARNING: Suspending script due to Caps Lock or Scroll Lock being on. Push CTRL+PAUSE/BREAK or mash CTRL+C to exit script.")
while GetKeyState(VK_CAPITAL) or GetKeyState(VK_SCROLL):
time.sleep(1)
# Get screenshots of face and submit them to worker threads
inputFile = os.path.join( root, file )
face = VamFace(inputFile)
for angle in angles:
face.setRotation(angle)
face.save( testJsonPath )
vamWindow.loadLook()
time.sleep(.3)
img = vamWindow.getScreenShot()
outputFileName = "{}_angle{}.png".format( os.path.splitext(os.path.basename(inputFile))[0], angle)
outputFileName = os.path.join( root, outputFileName )
poolWorkQueue.put( (img, outputFileName))
if pool is None:
worker_process_func(0, poolWorkQueue, doneEvent)
except:
print("Failed to process {}".format(file))
if not recursive:
break
print("Generator done!")
doneEvent.set()
if pool:
for proc in pool:
proc.join()
class Config:
CONFIG_VERSION = 1
def __init__(self, configJson, basePath=""):
minJson = os.path.join(
basePath,
configJson["minJson"]) if "minJson" in configJson else None
maxJson = os.path.join(
basePath,
configJson["maxJson"]) if "maxJson" in configJson else None
self._baseFace = VamFace(
os.path.join(basePath, configJson["baseJson"]), minJson, maxJson)
self._baseFace.trimToAnimatable()
self._paramShape = None
angles = set()
self._input_params = []
if "inputs" in configJson:
inputs = configJson["inputs"]
for param in inputs:
try:
paramName = param["name"]
paramList = []
for paramParam in param["params"]:
paramList.append({
"name": paramParam["name"],
"value": paramParam["value"]
})
if paramParam["name"] == "angle":
angles.add(float(paramParam["value"]))
self._input_params.append({
"name": paramName,
"params": paramList
})
except:
print("Error parsing parameter")
self._output_params = []
if "outputs" in configJson:
outputs = configJson["outputs"]
for param in outputs:
try:
paramName = param["name"]
paramList = []
for paramParam in param["params"]:
paramList.append({
"name": paramParam["name"],
"value": paramParam["value"]
})
if paramParam["name"] == "angle":
angles.add(float(paramParam["value"]))
self._output_params.append({
"name": paramName,
"params": paramList
})
except:
print("Error parsing parameter")
self._angles = list(angles)
self._angles.sort()
@staticmethod
def createFromFile(fileName):
data = open(fileName).read()
jsonData = json.loads(data)
if "config_version" in jsonData and jsonData[
"config_version"] is not Config.CONFIG_VERSION:
raise Exception(
"Config version mismatch! File was {}, reader was {}".format(
jsonData["config_version"], Config.CONFIG_VERSION))
return Config(jsonData, os.path.dirname(fileName))
def getBaseFace(self):
return self._baseFace
def getShape(self):
return self._paramShape
def getAngles(self):
return self._angles
def generateParams(self, relatedFiles):
if self._paramShape is None:
paramGen = ParamGenerator(self._input_params, self._angles,
relatedFiles, self._baseFace)
inputParams = paramGen.getParams()
inputLen = len(inputParams)
paramGen = ParamGenerator(self._output_params, self._angles,
relatedFiles, self._baseFace)
outputParams = paramGen.getParams()
outputLen = len(outputParams)
self._paramShape = (inputLen, outputLen)
outParams = inputParams + outputParams
else:
paramGen = ParamGenerator(self._input_params + self._output_params,
self._angles, relatedFiles,
self._baseFace)
outParams = paramGen.getParams()
return outParams