corrigindo erro em notbook

crossvalidation_augmentation_oversampling_for_object_detection.ipynb

@@ -93,14 +93,14 @@
       },
       "source": [
         "tipo_amostragem = 'cross' # repetition ou cross\n",
-        "percentual_aumento_dados = .1 # de .1 a 1\n",
+        "percentual_aumento_dados = 0 # de .1 a 1\n",
         "# se tipo_amostragem = 'cross', então deve ser 5 ou 10.\n",
         "# se tipo_amostragem = 'repetition', normalmente usa-se 30, 25, .., 10, 5 images para treinamento. O conjunto de teste é fixado em 70 imagens\n",
         "number_fold_or_image_train = 5  \n",
         "tem_validacao = True \n",
         "tem_oversampling = True\n",
         "\n",
-        "dataset_name = 'annotated_pests_v3'\n",
+        "dataset_name = 'annotated_pests_v3' #.zip\n",
         "path_dataset='/content/gdrive/MyDrive/datasets' # pasta existente no Drive\n"
       ],
       "execution_count": null,
@@ -122,7 +122,7 @@
       },
       "source": [
         "%cd /content\n",
-        "!git clone http://git.inovisao.ucdb.br/inovisao/crossvalidation-repetition-object-detection.git"
+        "!git clone http://git.inovisao.ucdb.br/inovisao/crossvalidation-repetition-object-detection.git\n"
       ],
       "execution_count": null,
       "outputs": []
@@ -170,7 +170,7 @@
         "parametros = '/content/' + dataset_name + ' /content/' + tipo_amostragem + ' ' + tipo_amostragem + ' ' + str(number_fold_or_image_train) + ' ' + str(tem_validacao) + ' ' + str(percentual_aumento_dados) + ' ' + str(tem_oversampling)\n",
         "comando = script + ' ' + parametros\n",
         "\n",
-        "%cd /content/crossvalidation-repetition\n",
+        "%cd /content/crossvalidation-repetition-object-detection\n",
         "!python3 $comando\n"
       ],
       "execution_count": null,
@@ -197,12 +197,9 @@
         "\n",
         "%cd /content/models/research\n",
         "!protoc object_detection/protos/*.proto --python_out=.\n",
-        "!cp object_detection/packages/tf1/setup.py .\n",
-        "#!cp object_detection/packages/tf2/setup.py .\n",
-        "!python -m pip install .\n",
-        "\n",
-        "#!python setup.py build\n",
-        "#!python setup.py install"
+        "#!cp object_detection/packages/tf1/setup.py .\n",
+        "!cp object_detection/packages/tf2/setup.py .\n",
+        "!python -m pip install .\n"
       ],
       "execution_count": null,
       "outputs": []
@@ -251,8 +248,7 @@
         "path_tfrecords = '/content/tfrecord'\n",
         "parametros = '/content/' + tipo_amostragem + ' ' + path_tfrecords + ' ' + '/content/detection_util_scripts'\n",
         "comando = script + ' ' + parametros\n",
-        "\n",
-        "%cd /content/crossvalidation-repetition\n",
+        "%cd /content/crossvalidation-repetition-object-detection\n",
         "!python3 $comando\n"
       ],
       "execution_count": null,
@@ -266,7 +262,7 @@
       "source": [
         "## Enviando as amostras para o Google Drive.\n",
         "\n",
-        "As amostras são enviadas para a pasta informada na variável **dataset_name** do diretório informado na variável **path_dataset** no Google Drive. Neste exemplo: /content/gdrive/MyDrive/datasets/annotated_pests_v3"
+        "As amostras são enviadas para a pasta informada na variável **dataset_name** do diretório informado na variável **path_dataset** no Google Drive. "
       ]
     },
     {
@@ -275,37 +271,27 @@
         "id": "lK1a1DazP1FV"
       },
       "source": [
-        "import os\n",
-        "from shutil import copyfile, make_archive\n",
-        "   \n",
-        "def transfere_files(fold_src_set, fold_dst_set):\n",
-        "  for f in os.listdir(fold_src_set):\n",
-        "    name, extension = os.path.splitext(f)\n",
-        "    if extension.lower() == '.pbtxt'.lower():\n",
-        "      file_src = fold_src_set + '/' + f\n",
-        "      file_dst = fold_dst_set + '/' + f\n",
-        "      copyfile(file_src, file_dst)\n",
-        "    if extension.lower() == '.tfrecord'.lower():\n",
-        "      file_src = fold_src_set + '/' + f\n",
-        "      file_dst = fold_dst_set + '/' + f\n",
-        "      copyfile(file_src, file_dst)\n",
+        "from files_utils import FileUtils\n",
+        "from yolo_utils import YoloUtils\n",
+        "\n",
+        "file_util = FileUtils()\n",
         "\n",
+        "#tranfere os arquivos .tfrecord e .pbtxt para a pasta do repositório\n",
         "repositorio = '/content/' + tipo_amostragem\n",
+        "file_util.transfereFilesTfrecord(path_tfrecords, repositorio)\n",
+        "\n",
+        "yo_utils = YoloUtils()\n",
+        "#quando rodar a yolo, os pesos serão salvos nesta pasta no drive. Configura o arquivo obj.data da yolo.\n",
+        "backup_weight_yolo = path_dataset+'/'+dataset_name\n",
+        "yo_utils.createFilesYolo(repositorio, backup_weight_yolo)\n",
+        "\n",
+        "path_douglasrizzo = '/content/detection_util_scripts'\n",
         "\n",
-        "#path_tfrecords = '/content/tfrecord'\n",
-        "for fold in os.listdir(path_tfrecords):\n",
-        "  fold_src = path_tfrecords + '/' + fold #origem\n",
-        "  fold_dst = repositorio + '/' + fold #destino\n",
-        "  for set_ in os.listdir(fold_src):\n",
-        "    fold_src_set = fold_src + '/' + set_ #origem\n",
-        "    fold_dst_set = fold_dst + '/' + set_ #destino\n",
-        "    if set_ != 'test':\n",
-        "      transfere_files(fold_src_set, fold_dst_set)\n",
+        "yo_utils.createAnnotationYolo(path_douglasrizzo, repositorio, path_tfrecords)\n",
         "\n",
-        "#eviando as amostras para o Drive\n",
-        "sample_name_zip = path_dataset + '/' + dataset_name + '/' + tipo_amostragem\n",
-        "origem = '/content/' + tipo_amostragem\n",
-        "make_archive(sample_name_zip, 'zip', origem)"
+        "#tranfere as amostras para a pasta do Drive\n",
+        "path_dst = path_dataset + '/' + dataset_name\n",
+        "file_util.transfereFilesDrive(repositorio, path_dst, tipo_amostragem)\n"
       ],
       "execution_count": null,
       "outputs": []