Small changes for testing, revert behind if bad

WorkingPyDemo.py

@@ -74,7 +74,8 @@ 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)[1:,:].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 = np.array(image_obj).astype(int)
     # 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]])
@@ -517,45 +518,50 @@ if __name__ == "__main__":
     scenes = file_extractor(folder_name)
     images = image_extractor(scenes)
     newnamesforlater = []
-    # list_dic, bins = make_dictionary(images[0:1], 4, False)
+    list_dic, bins = make_dictionary(images[19:20], 4, False)
     file_sizes_new = []
     file_sizes_old = []
-    list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
+    # list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
     bins = [21,32,48]
+    for i,item in enumerate(images):
+        if "NoI" in item:
+            print(item)
+            print(i)
     # np.save("first_dic.npy", list_dic)
-    for i in range(len(images[0:5])):
-        # image, new_error, diff = huffman(images[i], 4, False)
-        # encoded_string = encoder(new_error, list_dic, diff, bins)
-        # inletters = bitstring_to_bytes(encoded_string)
+    for i in range(19,len(images[0:20])):
+
+        image, new_error, diff = huffman(images[i], 4, False)
+        encoded_string = encoder(new_error, list_dic, diff, bins)
+        inletters = bitstring_to_bytes(encoded_string)
 
         if images[i][-5:] == ".tiff":
             newname = images[i][:-5]
         else:
             newname = images[i][:-4]
-        
+        print(newname)
         newnamesforlater.append(newname + "_Compressed.txt")
-        # with open(newname + "_Compressed.txt", 'wb') as f:
-        #     f.write(inletters)
+        with open(newname + "_Compressed.txt", 'wb') as f:
+            f.write(inletters)
         file_sizes_new.append((os.path.getsize(newname + "_Compressed.txt")))
         file_sizes_old.append((os.path.getsize(images[i])))
         # sleep(5)
         # if i % 50 == 0:
         #     print(i)
         #     sleep(20)
-    
+    print(np.sum(file_sizes_new)/np.sum(file_sizes_old))
     file_sizes_new.append(os.path.getsize("first_dic.npy"))
     print(np.sum(file_sizes_new)/np.sum(file_sizes_old))
     # list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
     bins = [21,32,48]
     
-    for i,item in enumerate(newnamesforlater):
-        print(item)
-        image, new_error, diff = huffman(images[i], 4, False)
-        encoded_string2 = bytes_to_bitstring(read_from_file(item))
-        starttime = time()
-        reconstruct_image = decoder(encoded_string2, list_dic, bins, False)
-        print(np.allclose(image, reconstruct_image))
-        print(time() - starttime)
+    # for i,item in enumerate(newnamesforlater):
+    #     print(item)
+    #     image, new_error, diff = huffman(images[i], 4, False)
+    #     encoded_string2 = bytes_to_bitstring(read_from_file(item))
+    #     starttime = time()
+    #     reconstruct_image = decoder(encoded_string2, list_dic, bins, False)
+    #     print(np.allclose(image, reconstruct_image))
+    #     print(time() - starttime)
     # text_to_tiff("images/1626033496_437803/1626033496_437803_3._Compressed.txt", list_dic, bins)
     # original_image = Image.open("images/1626033496_437803/1626033496_437803_3.tiff")
     # original_image = np.array(original_image)[1:]