global refactoring and fixes,

removed support of extracted(aligned) PNG faces. Use old builds to convert from PNG to JPG.

fanseg model file in facelib/ is renamed

core/leras/layers/Saveable.py

@@ -0,0 +1,103 @@
+import pickle
+from pathlib import Path
+from core import pathex
+import numpy as np
+
+from core.leras import nn
+
+tf = nn.tf
+
+class Saveable():
+    def __init__(self, name=None):
+        self.name = name
+
+    #override
+    def get_weights(self):
+        #return tf tensors that should be initialized/loaded/saved
+        return []
+
+    #override
+    def get_weights_np(self):
+        weights = self.get_weights()
+        if len(weights) == 0:
+            return []
+        return nn.tf_sess.run (weights)
+
+    def set_weights(self, new_weights):
+        weights = self.get_weights()
+        if len(weights) != len(new_weights):
+            raise ValueError ('len of lists mismatch')
+
+        tuples = []
+        for w, new_w in zip(weights, new_weights):
+
+            if len(w.shape) != new_w.shape:
+                new_w = new_w.reshape(w.shape)
+
+            tuples.append ( (w, new_w) )
+
+        nn.batch_set_value (tuples)
+
+    def save_weights(self, filename, force_dtype=None):
+        d = {}
+        weights = self.get_weights()
+
+        if self.name is None:
+            raise Exception("name must be defined.")
+
+        name = self.name
+        for w, w_val in zip(weights, nn.tf_sess.run (weights)):
+            w_name_split = w.name.split('/', 1)
+            if name != w_name_split[0]:
+                raise Exception("weight first name != Saveable.name")
+
+            if force_dtype is not None:
+                w_val = w_val.astype(force_dtype)
+
+            d[ w_name_split[1] ] = w_val
+
+        d_dumped = pickle.dumps (d, 4)
+        pathex.write_bytes_safe ( Path(filename), d_dumped )
+
+    def load_weights(self, filename):
+        """
+        returns True if file exists
+        """
+        filepath = Path(filename)
+        if filepath.exists():
+            result = True
+            d_dumped = filepath.read_bytes()
+            d = pickle.loads(d_dumped)
+        else:
+            return False
+
+        weights = self.get_weights()
+
+        if self.name is None:
+            raise Exception("name must be defined.")
+
+        tuples = []
+        for w in weights:
+            w_name_split = w.name.split('/')
+            if self.name != w_name_split[0]:
+                raise Exception("weight first name != Saveable.name")
+
+            sub_w_name = "/".join(w_name_split[1:])
+
+            w_val = d.get(sub_w_name, None)
+
+            if w_val is None:
+                #io.log_err(f"Weight {w.name} was not loaded from file {filename}")
+                tuples.append ( (w, w.initializer) )
+            else:
+                w_val = np.reshape( w_val, w.shape.as_list() )
+                tuples.append ( (w, w_val) )
+
+        nn.batch_set_value(tuples)
+
+        return True
+
+    def init_weights(self):
+        nn.init_weights(self.get_weights())
+    
+nn.Saveable = Saveable