enhancing landmarks extractor by using s3fd second pass inside second pass,

it will be x2 slower, but time will be saved due to more images will be marked properly
works on 2GB+

nnlib/device.py

@@ -64,6 +64,7 @@ class device:
                             
                 self.cpu_only = (len(self.gpu_idxs) == 0)
  
+            
             if not self.cpu_only:
                 self.gpu_names = []
                 self.gpu_compute_caps = []
@@ -73,7 +74,11 @@ class device:
                     self.gpu_compute_caps += [ device.getDeviceComputeCapability(gpu_idx) ]
                     self.gpu_vram_gb += [ device.getDeviceVRAMTotalGb(gpu_idx) ]
                 self.cpu_only = (len(self.gpu_idxs) == 0)
-                
+            else:
+                self.gpu_names = ['CPU']
+                self.gpu_compute_caps = [99]
+                self.gpu_vram_gb = [0]
+            
             if self.cpu_only:
                 self.backend = "tensorflow-cpu"