try.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from LanguageModels.appendQAModel import AppendQAModel\n",
    "from CLIPInterface.clipInterface import CLIPInterface\n",
    "from VQAInterface.vqaInterface import VQAInterface\n",
    "from CLIPVQA.clipvqa import CLIPVQA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "appendModel = AppendQAModel(separator = \" \", candidateAnswerGenerator = 'most_common')\n",
    "clipInterface = CLIPInterface(device = \"cpu\")\n",
    "vqaInterface = VQAInterface(dataDir = './data', versionType = \"v2\", taskType = \"OpenEnded\", dataType = \"mscoco\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = ['./data/Images/mscoco/val2014/COCO_val2014_000000000042.jpg', './data/Images/mscoco/val2014/COCO_val2014_000000000073.jpg', './data/Images/mscoco/val2014/COCO_val2014_000000000074.jpg']\n",
    "# l = ['./data/Images/mscoco/val2014/COCO_val2014_000000000042.jpg']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Batches processed: 100%|██████████| 2/2 [00:00<00:00,  5.37it/s]\n"
     ]
    }
   ],
   "source": [
    "allFeatures = clipInterface.getNormalisedImageFeatures(imageFilePath=l, batch_size=1, pklFilePath='./test.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.25994962, 0.7400503 ]], dtype=float32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clipInterface.getProbs(imageFilePath='./data/Images/mscoco/val2014/COCO_val2014_000000000073.jpg', texts = ['yes', 'no'])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ip = vqaInterface.getImagePaths(dataSubType='val2014')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle as pkl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = pkl.load(open('./test.pkl', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       dtype=float32),\n",
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       "       dtype=float32)}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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