first progress on inputlayer

.gitignore

@@ -89,5 +89,4 @@ ENV/
 .ropeproject
 
 # tensorflow data
-data/*
 output/*

data/.gitignore

@@ -0,0 +1 @@
+mnist/

inputlayer/__init__.py

@@ -0,0 +1,2 @@
+from .inputlayer import InputLayer
+from .opencv import OpenCVInputLayer

inputlayer/inputlayer.py

@@ -0,0 +1,23 @@
+# -*- coding: utf-8 -*-
+
+class InputLayer:
+    """
+    Contains the worker thread that uses OpenCV to feed in images and video feeds to TF.
+    """
+
+    def assertions(self):
+        assert(42==42)
+
+    def __init__(self):
+        self.assertions()
+        self.callbacks = []
+        print ("📸 Input Layer initalized")
+
+    def registerCallback(self, region, callback):
+        ##assert callback is a function
+        self.callbacks.append([region, callback])
+        print ("📸 callback registered")
+
+
+    def deregisterCallback(self, callback):
+        raise NotImplementedError()

inputlayer/opencv.py

@@ -0,0 +1,42 @@
+# -*- coding: utf-8 -*-
+import cv2
+from . import InputLayer
+
+class OpenCVInputLayer(InputLayer):
+    """
+    Contains the worker thread that uses OpenCV to feed in images and video feeds to TF.
+    """
+
+    def feedWebcam(self):
+        cap = cv2.VideoCapture(0)
+
+        while(True):
+            isvalid, frame = cap.read()
+            if isvalid:
+                res = cv2.resize(frame,(32, 32), interpolation = cv2.INTER_CUBIC)
+                gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
+                self.processFrame(gray)
+            else:
+                break
+
+    def feedVideo(self, filename):
+        cap = cv2.VideoCapture(filename)
+
+        while(True):
+            isvalid, frame = cap.read()
+            if isvalid:
+                res = cv2.resize(frame,(32, 32), interpolation = cv2.INTER_CUBIC)
+                gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
+                self.processFrame(gray)
+            else:
+                break
+
+    def processFrame(self, frame):
+        for region, callback in self.callbacks:
+            x = region[0]
+            y = region[1]
+            w = region[2]
+            h = region[3]
+            callback(frame[y:y + h, x:x + w])
+        #iterate callbacks and split into corresponding regions
+        #triggercallbacks

manual_4_stream_input.py

@@ -1,43 +1,67 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
-#from sklearn import datasets
 from model import StackedAutoEncoder
-import matplotlib.pyplot as plt
+from inputlayer import OpenCVInputLayer
 
 import tensorflow as tf
-from tensorflow.examples.tutorials.mnist import input_data
-mnist = input_data.read_data_sets('data/mnist', one_hot=True)
+#from tensorflow.examples.tutorials.mnist import input_data
+#mnist = input_data.read_data_sets('data/mnist', one_hot=True)
 
 import numpy as np
 import model.utils as utils
 from os.path import join as pjoin
 
-#utils.start_tensorboard()
 
-train_data = mnist.train.images 
+import cv2
+#utils.start_tensorboard()
 
-print "👉 processed input data!"
+#train_data = mnist.train.images 
+#print "👉 processed input data!"
 
 print "recording summaries to " + utils.get_summary_dir()
 
+
 models = []
 
 for _ in xrange(4):
     models.append(StackedAutoEncoder(
-        dims=[100, 100],
-        activations=['linear', 'linear'], 
+        dims=[100],
+        activations=['linear'], 
         noise='gaussian', 
-        epoch=[100, 100],
+        epoch=[10],
         loss='rmse',
         lr=0.007,
-        batch_size=150
+        batch_size=1
     ))
 
+### Initialize Enqueue thread:
+inputlayer = OpenCVInputLayer()
+
+inputlayer.registerCallback([00,00,16,16], models[0].fit)
+inputlayer.registerCallback([16,00,16,16], models[1].fit)
+inputlayer.registerCallback([00,16,16,16], models[2].fit)
+inputlayer.registerCallback([16,16,16,16], models[3].fit)
+
+inputlayer.feedWebcam()
+
+
+
+
+
+"""
 for i in xrange(2):
     for model in models:
         model.fit(train_data)
         model.save_parameters()
         
 for model in models:
-    model.write_activation_summary()
+    model.write_activation_summary()
+"""
+
+
+
+
+
+
+

model/stacked_autoencoder.py

@@ -33,8 +33,7 @@ def assertions(self):
         assert utils.noise_validator(
             self.noise, allowed_noises), "Incorrect noise given"
 
-    def __init__(self, dims, activations, epoch=1000, noise=None, loss='rmse',
-                 lr=0.001, batch_size=100, session=None):
+    def __init__(self, dims, activations, epoch=1000, noise=None, loss='rmse', lr=0.001, batch_size=100, session=None):
         self.batch_size = batch_size
         self.lr = lr
         self.loss = loss