fixed issue where non-binary images where in dataset at the cost of .bmp increasing the size by 2. Made it so id.py prevents their future inclusion.

initdb.sh

@@ -1 +1 @@
-cat ./src/db/schema/schema.sql | sqlite3 ./src/dbmariokart.db
+cat ./src/db/schema/schema.sql | sqlite3 ./src/db/mariokart.db

src/id.py

@@ -3,7 +3,8 @@ from PIL import Image
 import base64
 import sqlite3
 import hashlib
-
+import numpy as np
+from lib.dbtools import print_image
 #This is a much updated version of the older ID. This one marks the exit from the ascii days of this project
 #As did before. you add your images into id/x (1 .. 2 .. 3), and include a bunch. One full black, and one full white at the bare minimum
 #this generates a 0 and 1 representation of that data allowing for classifying. the images based upon this data.
@@ -14,7 +15,6 @@ rank_to_pixelarray = {}
 for digit in range(1, 13):
     one_holder = []
     images = []
-    binary = []
     base = f"id/{digit}"
     files = os.listdir(base)
     im = Image.open(f'{base}/{files[0]}')
@@ -29,26 +29,26 @@ for digit in range(1, 13):
             for image in images:
             #because of the binary image setup, it only returns 1 value.
             #encase it isn't binary
-                if type(image[0,0]) != int: 
-                    if image[x,y][0] == 0:
-                        binary.append(0)
-                        break
-                if image[x,y] == 0:
-                    binary.append(0)
+                value = image[x,y]
+                if type(value) == tuple:
+                    value = value[0]
+
+                if value != 255:
                     break
+
+                assert value != 255 or value != 0
+                    
             #for-elses only execute if the for loop doesn't break 
             else:
-                binary.append(1)
                 one_holder.append((x,y))
 
-    for x in range(0, im.size[1]):
-        holder = []
-        for y in range(0, im.size[0]):
-            holder.append(str(binary[(x*im.size[0])+y]))
-        print("".join(holder))
+    empty = np.zeros((im.size[0], im.size[1]), dtype=np.uint8)
+
+    for x in one_holder:
+        empty[x] = 1
+    print_image(empty, inverted=True)
     rank_to_pixelarray[digit] = one_holder
 
-#I'm afraid python may oneday change the __str__ for Dict and then this will create a version issue... 
 raw_string = str(rank_to_pixelarray)
 encoded = raw_string.encode('ascii')
 base64_encoded = base64.b64encode(encoded)

src/lib/compile.py

@@ -14,7 +14,7 @@ import lz4.frame
 import sqlite3
 import hashlib
 from lib.classes import RankEvent, ProcessReturn, State
-debug = False
+debug = True
 
 
 def get_2d_value(n, width):
@@ -56,11 +56,7 @@ def deserialize_bitfield_video(bit_array, height, width):
     return np.unpackbits(frames).reshape((output_frame_count, height, width))
 
 
-def print_image(a):
-    for row in np.rollaxis(a, 0, 0):
-        pythonified = row.tobytes()
-        output = map(lambda x: str(int(int(x) == 1)), pythonified)
-        print(''.join(output))
+
 
 def process_ranks(events : List[RankEvent], minimum_length : int):
     #Removes transients of a given amount

src/lib/dbtools.py

@@ -2,19 +2,11 @@ import sqlite3
 import matplotlib.pyplot as plt
 import pickle
 import more_itertools as it
-from compile import deserialize_bitfield_frame, print_image, deserialize_bitfield_video, compile
+from lib.compile import deserialize_bitfield_frame, deserialize_bitfield_video, compile
 import lz4.frame
 import cv2
 import numpy as np
-con = sqlite3.connect("../db/mariokart.db")
-race_id = 7
-cur = con.cursor()
-class mock_state():
-    def __init__(self, video_data, channel_name, date):
-        self.video_data = video_data
-        self.channel_name = channel_name
-        self.date = date
-
+from lib.classes import State
 def get_archived_video(con, cur, race_id):
     video_prepare = cur.execute("select VideoDataBinaryLZ4 from Race where Id = ? ", (race_id,))
     video = video_prepare.fetchall()[0][0]
@@ -37,9 +29,17 @@ def recompile(cur, con, race_id, model_id):
     info_prepare = cur.execute("select UploadDate, Uploader from Race where Id = ? ", (race_id,))
     date, channel_name = info_prepare.fetchone()
     video_data = prepare_video_for_export(get_archived_video(con, cur, race_id))
-    state = mock_state(video_data, channel_name, date)
+    state = State(channel_name, date, "./db/mariokart.db")
+    state.video_data = video_data
     compile(state, model_id=model_id, recompile=True, race_id=race_id)
 
+def print_image(a, inverted = False):
+    axis = 0
+    if inverted: axis = 1
+    for row in np.rollaxis(a, axis, 0):
+        pythonified = row.tobytes()
+        output = map(lambda x: str(int(int(x) == 1)), pythonified)
+        print(''.join(output))
 #recompile(con, cur, 7, -1)
 #for_export = prepare_video_for_export(get_archived_video(con, cur, race_id))
 #data = np.concatenate(np.concatenate(for_export[583:583+20].reshape(4, 5, 80, 110), axis=1), axis=1)