Train local attention model

dattran2346 · Feb 3, 2019 · 4737199 · 4737199
1 parent 2662f35
commit 4737199
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Showing 23 changed files with 1,178 additions and 2,272 deletions.
diff --git a/src/Heatmap.ipynb b/src/Heatmap.ipynb
diff --git a/src/CAM.ipynb → src/Old CAM.ipynb b/src/CAM.ipynb → src/Old CAM.ipynb
@@ -5,17 +5,69 @@
    "execution_count": 1,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%reload_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Generate CAM (Class Activation Map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline\n",
     "import pandas as pd\n",
     "from constant import CSV_DIR, CLASS_NAMES\n",
-    "import numpy as np"
+    "import numpy as np\n",
+    "\n",
+    "from fastai.conv_learner import *\n",
+    "# import pixiedust\n",
+    "from matplotlib.patches import Rectangle\n",
+    "from datetime import datetime\n",
+    "import pandas as pd\n",
+    "\n",
+    "import torch\n",
+    "from layers import *\n",
+    "from constant import CLASS_NAMES\n",
+    "from transform import chest_xray_transfrom\n",
+    "from metrics import *\n",
+    "import pretrainedmodels\n",
+    "from recorder import TrainingRecoder\n",
+    "import pretrainedmodels\n",
+    "from dataset import ChestXray14Dataset\n",
+    "from model_data import ModelData\n",
+    "from chexnet import ChexNet"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "PATH = Path('/home/dattran/data/xray-thesis/chestX-ray14')\n",
+    "IMAGE_DN = 'images'\n",
+    "IMAGE_NAME = '00007551_000.png'\n",
+    "sz = 224\n",
+    "\n",
+    "    \n",
+    "densenet = pretrainedmodels.__dict__['densenet121']()\n",
+    "tfms = chest_xray_transfrom(densenet, sz, .875)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -32,6 +84,25 @@
     "    plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class FeatureHook:\n",
+    "    features = None\n",
+    "    \n",
+    "    def __init__(self, m):\n",
+    "        self.hook = m.register_forward_hook(self.hook_fn)\n",
+    "    \n",
+    "    def hook_fn(self, module, input, output):\n",
+    "        self.features = output\n",
+    "        \n",
+    "    def remove(self):\n",
+    "        self.hook.remove()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -1097,7 +1168,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.6"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,