{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4b48236b-3e6f-4dec-ac45-5bb8c5f7ff45",
   "metadata": {},
   "source": [
    "<div style=\"font-size: 50px; text-align: center\" >Deadpool™️ Detector</div>\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "731ffedc-3131-4d20-bed6-ecfcf0681d73",
   "metadata": {},
   "source": [
    "# Description\n",
    "First development app using deep learning techniques. Stepping stone in my journey.\n",
    "\n",
    "Given an image infer if it contains Deadpool in it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1afbc8dd-8b83-4603-8ab8-3724fca03fa3",
   "metadata": {},
   "source": [
    "# Train a model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e2cfb0c-6ac4-4cd3-b66e-1eed809bb88d",
   "metadata": {},
   "source": [
    "## Training Data\n",
    "Using [SH2022 Dataset](https://www.kaggle.com/datasets/muhammadhananasghar/sh2022-dataset) there is a labeled set of Deadpool images."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2549da81-e133-4f5d-93e2-e754885d9d99",
   "metadata": {},
   "source": [
    "Add data to a `DataLoaders` object and display a batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9fa3c5f-c90f-44bb-bf95-cfbc9698c97e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "\n",
    "data_path = Path('/home/zeus/data/SH2022')\n",
    "\n",
    "dls = ImageDataLoaders.from_folder(\n",
    "    path=data_path,\n",
    "    train='train',\n",
    "    valid='test/Deadpool',\n",
    "    item_tfms=Resize(224),\n",
    "    batch_tfms=aug_transforms()\n",
    ")\n",
    "dls.show_batch()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4b6eb81-25b6-449c-8f48-f418c6e1cb7a",
   "metadata": {},
   "source": [
    "## Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54353c83-2bf3-419d-a7f3-24eb6feef718",
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = vision_learner(dls, resnet34, metrics=error_rate)\n",
    "learn.fine_tune(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f5afdb5-998b-4b12-b56f-0c89077ae5c2",
   "metadata": {},
   "source": [
    "## Export Trained Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22ff7ee5-efc0-4c71-88e6-c1a43b94edba",
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.export('/home/zeus/projects/Deadpool-Detector/deadpool-detection-model.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "792d8a70",
   "metadata": {},
   "source": [
    "## Share Learner with the world!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "27376bb5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "14796a3e",
   "metadata": {},
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       "Upload 1 LFS files:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
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      "text/plain": [
       "model.pkl:   0%|          | 0.00/88.7M [00:00<?, ?B/s]"
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     "metadata": {},
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    {
     "data": {
      "text/plain": [
       "'https://huggingface.co/jeffreymjohnson/Deadpool-Detector/tree/main/'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from huggingface_hub import push_to_hub_fastai\n",
    "\n",
    "learn = load_learner('/home/zeus/projects/Deadpool-Detector/deadpool-detection-model.pkl')\n",
    "repo_id = \"jeffreymjohnson/Deadpool-Detector\"\n",
    "push_to_hub_fastai(learner=learn, repo_id=repo_id)"
   ]
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  {
   "cell_type": "markdown",
   "id": "61b3019d-cd37-49b4-bced-503499796d6c",
   "metadata": {},
   "source": [
    "# Create App"
   ]
  },
  {
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   ],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "from huggingface_hub import from_pretrained_fastai\n",
    "\n",
    "learn = from_pretrained_fastai(\"jeffreymjohnson/Deadpool-Detector\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cc0fa8a2-51fe-4591-9056-e84e0fec9af7",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'learn' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[2], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m#|export\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m labels \u001b[38;5;241m=\u001b[39m \u001b[43mlearn\u001b[49m\u001b[38;5;241m.\u001b[39mdls\u001b[38;5;241m.\u001b[39mvocab\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpredict\u001b[39m(img):\n\u001b[1;32m      4\u001b[0m     yes_reaction \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreactions/yes.jfif\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'learn' is not defined"
     ]
    }
   ],
   "source": [
    "#|export\n",
    "labels = learn.dls.vocab\n",
    "def predict(img):\n",
    "    yes_reaction = \"reactions/yes.jfif\"\n",
    "    no_reaction = \"reactions/no.jfif\"\n",
    "    what_reaction = \"reactions/what.jpg\"\n",
    "    \n",
    "    img = PILImage.create(img)\n",
    "    pred,pred_idx,probs = learn.predict(img)\n",
    "    index = pred_idx.item()\n",
    "    probability = probs[index].item()\n",
    "    isDeadpool = pred == \"Deadpool\"\n",
    "    \n",
    "    if isDeadpool:\n",
    "        x = \"is\"\n",
    "    else:\n",
    "        x = \"is not\"\n",
    "    \n",
    "    #print(\"The probability is: [\" + str(probability) + \"] that this \" + x + \" Deadpool\")\n",
    "    \n",
    "    if probability < .75:\n",
    "        return PILImage.create(what_reaction)\n",
    "    elif isDeadpool:\n",
    "        return PILImage.create(yes_reaction)\n",
    "    else:\n",
    "        return PILImage.create(no_reaction)"
   ]
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     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "Running on public URL: https://ed025bd9d3a5e5798f.gradio.live\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n"
     ]
    },
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       "<div><iframe src=\"https://ed025bd9d3a5e5798f.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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     "text": [
      "The probability is: [0.9999980926513672] that this is Deadpool\n"
     ]
    },
    {
     "data": {
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       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
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     "text": [
      "The probability is: [0.9999998807907104] that this is not Deadpool\n"
     ]
    }
   ],
   "source": [
    "#|export\n",
    "import gradio as gr\n",
    "\n",
    "demo = gr.Interface(\n",
    "    title=\"Deadpool™️ Detector\",\n",
    "    fn=predict,\n",
    "    inputs=gr.Image(shape=(200,200)),\n",
    "    outputs=gr.Image(shape=(200,200)), \n",
    "    examples=[\"examples/deadpool_example1.jpg\", \"examples/deadpool_example2.jpg\", \"examples/deadpool_example3.jpg\", \"examples/spiderman.jpg\",]\n",
    ").launch(share=true)"
   ]
  },
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