more renamings

FullTester.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,21 +15,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "5\n",
-      "5\n",
-      "0.30596738362283216\n"
+      "521\n",
+      "263\n",
+      "0.4041653243824837\n"
      ]
     }
    ],
    "source": [
-    "scenes = file_extractor(\"betterimages\")\n",
+    "scenes = file_extractor(\"images\")\n",
     "images = image_extractor(scenes)\n",
     "print(len(images))\n",
     "newnamesforlater = []\n",
@@ -48,8 +48,8 @@
     "    # with open(newname + \"_Compressed.txt\", 'wb') as f:\n",
     "    #     f.write(inletters)\n",
     "        file_sizes_new.append((os.path.getsize(newname + \"_Compressed.txt\")))\n",
-    "        # file_sizes_old.append((os.path.getsize(newname + \"RemovedFirstLine\" + \".tif\")))\n",
-    "        file_sizes_old.append((os.path.getsize(newname + \".tiff\")))\n",
+    "        file_sizes_old.append((os.path.getsize(newname + \"RemovedFirstLine\" + \".tif\")))\n",
+    "        # file_sizes_old.append((os.path.getsize(newname + \".tiff\")))\n",
     "file_sizes_new.append(os.path.getsize(\"first_dic.npy\"))\n",
     "print(len(newnamesforlater))\n",
     "print(np.sum(file_sizes_new)/np.sum(file_sizes_old))\n"
@@ -601,14 +601,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "263\n",
+      "521\n",
       "263\n"
      ]
     }

WorkingPyDemo.py

@@ -75,7 +75,7 @@ def predict_pix(tiff_image_path, difference = True):
     A       ndarray(3 X 3): system of equation
     """
     image_obj = Image.open(tiff_image_path)    #Open the image and read it as an Image object
-    image_array = np.array(image_obj).astype(int)    #Convert to an array, leaving out the first row because the first row is just housekeeping data
+    image_array = np.array(image_obj)[1:].astype(int)    #Convert to an array, leaving out the first row because the first row is just housekeeping data
     # image_array = image_array.astype(int) 
     # A = np.array([[3,0,-1],[0,3,3],[1,-3,-4]]) # the matrix for system of equation
     Ainv = np.array([[0.5,-0.5,-0.5],[-0.5,1.83333333,1.5],[0.5,-1.5,-1.5]])
@@ -523,8 +523,8 @@ if __name__ == "__main__":
     file_sizes_old = []
     # list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
     bins = [21,32,48]
-    np.save("second_dic.npy", list_dic)
-    for i in range(len(images)):
+    np.save("first_dict.npy", list_dic)
+    for i in range(0,3):
 
         image, new_error, diff = huffman(images[i], 4, False)
         encoded_string = encoder(new_error, list_dic, diff, bins)