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   "execution_count": 1,
   "id": "fa37d83b-2543-4b97-a6dd-f54fc56bfd9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import streamlit as st\n",
    "import torch\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import torch.nn.functional as F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cfa28009-cc5a-42bf-a5a9-b1cbaeb09fa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import custom modules\n",
    "from models.resnet_model import MalariaResNet50\n",
    "from gradcam import visualize_gradcam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4dbb399f-01b7-4143-97d0-0fc4b1a33148",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-28 22:57:39.942 WARNING streamlit.runtime.scriptrunner_utils.script_run_context: Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:39.948 WARNING streamlit.runtime.scriptrunner_utils.script_run_context: Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.270 \n",
      "  \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n",
      "  command:\n",
      "\n",
      "    streamlit run C:\\Users\\HP\\miniconda3\\envs\\pytorch_env\\lib\\site-packages\\ipykernel_launcher.py [ARGUMENTS]\n",
      "2025-05-28 22:57:41.272 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.274 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.275 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
     ]
    }
   ],
   "source": [
    "st.set_page_config(page_title=\"🧬 Malaria Cell Classifier\", layout=\"wide\")\n",
    "st.title(\"🧬 Malaria Cell Classifier with Grad-CAM\")\n",
    "st.write(\"Upload a blood smear image and the model will classify it as infected or uninfected, and highlight key regions using Grad-CAM.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cfba0e0a-094e-491f-8d7b-abe0643344dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-28 22:57:41.317 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.319 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.320 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.833 Thread 'Thread-3': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:41.840 Thread 'Thread-3': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/resnet50-11ad3fa6.pth\" to C:\\Users\\HP/.cache\\torch\\hub\\checkpoints\\resnet50-11ad3fa6.pth\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████| 97.8M/97.8M [00:09<00:00, 11.2MB/s]\n",
      "2025-05-28 22:57:53.490 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:53.497 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
     ]
    }
   ],
   "source": [
    "# Load Model\n",
    "@st.cache_resource\n",
    "def load_model():\n",
    "    model = MalariaResNet50(num_classes=2)\n",
    "    model.load_state_dict(torch.load(\"models/malaria_model.pth\", map_location=torch.device('cpu')))\n",
    "    model.eval()\n",
    "    return model\n",
    "\n",
    "model = load_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "11f5d404-6c4c-4484-a11a-acede1e5ab7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-28 22:57:53.586 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:53.592 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:53.594 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:53.600 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
      "2025-05-28 22:57:53.606 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
     ]
    }
   ],
   "source": [
    "# Upload Image\n",
    "uploaded_file = st.file_uploader(\"Choose an image...\", type=[\"jpg\", \"png\", \"jpeg\"])\n",
    "\n",
    "if uploaded_file is not None:\n",
    "    # Save uploaded image temporarily\n",
    "    temp_image_path = f\"temp_{uploaded_file.name}\"\n",
    "    with open(temp_image_path, \"wb\") as f:\n",
    "        f.write(uploaded_file.getbuffer())\n",
    "\n",
    "    # Display original image\n",
    "    image = Image.open(uploaded_file).convert(\"RGB\")\n",
    "    st.image(image, caption=\"Uploaded Image\", use_column_width=True)\n",
    "\n",
    "    # Predict button\n",
    "    if st.button(\"Predict\"):\n",
    "        with st.spinner(\"Classifying...\"):\n",
    "            # Run prediction and show Grad-CAM\n",
    "            pred_label, confidence = model.predict(temp_image_path, device='cpu', show_image=False)\n",
    "            \n",
    "            st.success(f\"✅ Prediction: **{pred_label}** | Confidence: **{confidence:.2%}**\")\n",
    "\n",
    "            # Show Grad-CAM\n",
    "            st.subheader(\"🔍 Grad-CAM Visualization\")\n",
    "            visualize_gradcam(model, temp_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8fa9705e-7775-489a-ad09-27e96793dcc3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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