Upload fusion_t2i_CLIP_interrogator.ipynb

Google Colab Notebooks/fusion_t2i_CLIP_interrogator.ipynb

@@ -387,11 +387,6 @@
       "cell_type": "code",
       "source": [
         "# @title \t⚄ Use a pre-encoded prompt + image pair from the fusion gen (note: NSFW!)\n",
-        "\n",
-        "#image_index = 0 # @param {type:'number'}\n",
-        "# @markdown 📥 Load the data (only required one time)\n",
-        "load_the_data = True # @param {type:\"boolean\"}\n",
-        "\n",
         "# @markdown 🖼️ Choose a pre-encoded reference\n",
         "index = 708 # @param {type:\"slider\", min:0, max:1666, step:1}\n",
         "\n",
@@ -407,9 +402,47 @@
         "strength = 1 # @param {type:\"slider\", min:-5, max:5, step:0.1}\n",
         "\n",
         "# @markdown Calculate most similiar items using above settings?\n",
-        "enable = False # @param {type:\"boolean\"}\n",
         "\n",
-        "if (load_the_data):\n",
+        "\n",
+        "# @title ⚙️📝 Print the results (Advanced)\n",
+        "list_size = 1000 # param {type:'number'}\n",
+        "start_at_index = 0 # param {type:'number'}\n",
+        "print_Similarity = True # param {type:\"boolean\"}\n",
+        "print_Prompts = True # param {type:\"boolean\"}\n",
+        "print_Prefix = True # param {type:\"boolean\"}\n",
+        "print_Descriptions = True # param {type:\"boolean\"}\n",
+        "compact_Output = True # param {type:\"boolean\"}\n",
+        "\n",
+        "# @markdown -----------\n",
+        "# @markdown 📝 Printing options\n",
+        "newline_Separator = False # @param {type:\"boolean\"}\n",
+        "\n",
+        "import random\n",
+        "list_size2 = 1000 # param {type:'number'}\n",
+        "start_at_index2 = 10000 # param {type:'number'}\n",
+        "rate_percent  = 0 # param {type:\"slider\", min:0, max:100, step:1}\n",
+        "\n",
+        "# @markdown Repeat output N times\n",
+        "N = 7 # @param {type:\"slider\", min:0, max:10, step:1}\n",
+        "\n",
+        "#image_index = 0 # @param {type:'number'}\n",
+        "# @markdown 📥 Reload vocab (required if you change the vocab)\n",
+        "reload_vocab = False # @param {type:\"boolean\"}\n",
+        "_load_the_data = reload_vocab\n",
+        "\n",
+        "#image_index = 0 # @param {type:'number'}\n",
+        "# @markdown ⚙️ Do dot product calculation (disable if you only want to browse images)\n",
+        "run_script = True # @param {type:\"boolean\"}\n",
+        "enable = run_script\n",
+        "\n",
+        "\n",
+        "# Load the data if not already loaded\n",
+        "try:\n",
+        "    loaded2\n",
+        "except:\n",
+        "  _load_the_data = True\n",
+        "\n",
+        "if (_load_the_data):\n",
         "  target_prompts , target_text_encodings , urls , target_image_encodings , NUM_ITEMS =  getPromptsAndLinks('/content/text-to-image-prompts/fusion')\n",
         "  from transformers import AutoTokenizer\n",
         "  tokenizer = AutoTokenizer.from_pretrained(\"openai/clip-vit-large-patch14\", clean_up_tokenization_spaces = False)\n",
@@ -459,27 +492,6 @@
         "  # Sort the items\n",
         "  sorted , indices = torch.sort(sims,dim=0 , descending=True)\n",
         "\n",
-        "  # @title ⚙️📝 Print the results (Advanced)\n",
-        "  list_size = 1000 # param {type:'number'}\n",
-        "  start_at_index = 0 # param {type:'number'}\n",
-        "  print_Similarity = True # param {type:\"boolean\"}\n",
-        "  print_Prompts = True # param {type:\"boolean\"}\n",
-        "  print_Prefix = True # param {type:\"boolean\"}\n",
-        "  print_Descriptions = True # param {type:\"boolean\"}\n",
-        "  compact_Output = True # param {type:\"boolean\"}\n",
-        "\n",
-        "  # @markdown -----------\n",
-        "  # @markdown ⚙️📝 Printing options\n",
-        "  newline_Separator = False # @param {type:\"boolean\"}\n",
-        "\n",
-        "  import random\n",
-        "  list_size2 = 1000 # param {type:'number'}\n",
-        "  start_at_index2 = 10000 # param {type:'number'}\n",
-        "  rate_percent  = 0 # param {type:\"slider\", min:0, max:100, step:1}\n",
-        "\n",
-        "  # @markdown Repeat output N times\n",
-        "  N = 7 # @param {type:\"slider\", min:0, max:10, step:1}\n",
-        "\n",
         "  # title Show the 100 most similiar suffix and prefix text-encodings to the text encoding\n",
         "  RANGE = list_size\n",
         "  separator = '|'\n",