some small organizations

S0_PrepareDataset.py

@@ -4,6 +4,7 @@ import tarfile
 import requests
 from tqdm import tqdm
 import os
+from pathlib import Path
 from joblib import Parallel, delayed
 
 def listdir_full(path: str) -> list[str]:
@@ -26,6 +27,7 @@ def download_file(url, pos):
                             p_bar.update(len(chunk))
     return local_filename
 
+Path("data").mkdir(exist_ok=True)
 IMAGE_DIR = "data/image"
 if not os.path.isdir(IMAGE_DIR):
     links = ["http://www.inf.ufpr.br/lesoliveira/download/macroscopic0.zip",

S6_Evaluation 2.ipynb

@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,7 +128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -622,20 +622,9 @@
        "40         96  "
       ]
      },
-     "execution_count": 88,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
-      "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
-      "\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
-      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
-     ]
     }
    ],
    "source": [
@@ -648,17 +637,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 312/312 [01:19<00:00,  3.92it/s]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "test_loader = DataLoader(TimberDataset(test_df, is_train=True,transform=transform),\n",
     "                            batch_size=12)\n",
@@ -669,7 +650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -707,16 +688,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "312"
+       "50"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -727,7 +708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -756,7 +737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -1250,7 +1231,7 @@
        "40          8  "
       ]
      },
-     "execution_count": 85,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1259,6 +1240,15 @@
     "zipped = zip(os.listdir(\"data/image/test\"), accuracy, recall, precision, f1s, class_count)\n",
     "pd.DataFrame(zipped, columns=[\"Name\", \"Accuracy\", \"Recall\", \"Precision\", \"F1-Score\", \"N Samples\"])"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.DataFrame(zipped, columns=[\"Name\", \"Accuracy\", \"Recall\", \"Precision\", \"F1-Score\", \"N Samples\"])"
+   ]
   }
  ],
  "metadata": {

data/annotations.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:64dfe7d6b4be6d3efa7b52c5919eebb8068d53fba555f585b401ece80779db0f
-size 81559

data/coco.yaml

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:65cc8c22fc16910f500b4dbfa1660dccabad9acc2bab1e670fd379c96a6aad72
-size 1310

data/dataset.yaml

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:586efc12ccc267f70359b3fb245f93effe57891ca53734fb0f8d9c0c9d32c9b6
-size 1258

data/timber.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:137eb7516924d5d0c6a3921d54b294e95f506e58c853339d428a810901d5124e
-size 1605

data/voc.yaml

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f496796f480b640ded3931ed83e499bdf269f96dedbb55272674fb81825a3fdc
-size 612