Made all processes threaded. Also changed up the neural network to hopefully better support the higher class load

1 - ImageGatherer.py

@@ -3,23 +3,26 @@ import multiprocessing
 
 from google_images_download import google_images_download
 
-df = pd.read_csv("pokemon.csv")
-
-response = google_images_download.googleimagesdownload()
-
 
 def get_images_for_pokemon(pokemon):
+    response = google_images_download.googleimagesdownload()
     response.download(
         {
-            "keywords": pokemon,# + " pokemon",
+            "keywords": pokemon + " pokemon",
             "limit": 250,
             "chromedriver": "chromedriver",
-            "thumbnail":True
-        #     Add chromedriver to your path or just point this var directly to your chromedriver
+            "thumbnail": True
+            #     Add chromedriver to your path or just point this var directly to your chromedriverv
         }
     )
 
-pool = multiprocessing.Pool(multiprocessing.cpu_count()*4)
 
-pool.map(get_images_for_pokemon, df["identifier"][:490])
+    # freeze_support()
+    df = pd.read_csv("pokemon.csv")
 
+    pool = multiprocessing.Pool(multiprocessing.cpu_count()*3)
+    fixes = []
+    pool.map(get_images_for_pokemon, [fixes])#df["identifier"]
+
+    # for pokemon in df["identifier"][:490]:
+    #     get_images_for_pokemon(pokemon)