a

Machine_Learning/notebook.ipynb

@@ -24,6 +24,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "94627f52",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,6 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "bad56dcc",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -80,6 +82,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "83235964",
    "metadata": {},
    "source": [
     "## 2. Download dan Ekstraksi Dataset"
@@ -88,6 +91,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "c18354b4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -126,6 +130,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "5e19a255",
    "metadata": {},
    "source": [
     "## 3. Data Cleaning dan Validasi Gambar (RGB)"
@@ -134,13 +139,23 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "63ee82cc",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# --- Determine dataset path ---\n",
+    "# Colab: zip extracts to dataset/ with dataset_jagung_v1/ subfolder\n",
+    "# Local: zip extracts classes directly to dataset/\n",
     "if IS_COLAB:\n",
     "    dataset_path = \"/content/dataset/dataset_jagung_v1\"\n",
     "else:\n",
-    "    dataset_path = os.path.join(extract_path, \"dataset_jagung_v1\")\n",
+    "    candidate = os.path.join(extract_path, \"dataset_jagung_v1\")\n",
+    "    if os.path.isdir(candidate):\n",
+    "        dataset_path = candidate\n",
+    "    else:\n",
+    "        dataset_path = extract_path  # classes are directly in dataset/\n",
+    "\n",
+    "print(f\"Dataset path: {dataset_path}\")\n",
     "\n",
     "def clean_image_data(directory):\n",
     "    removed_count = 0\n",
@@ -167,6 +182,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "c93f0a16",
    "metadata": {},
    "source": [
     "## 4. Data Splitting (Train:Validation:Test = 70:15:15)"
@@ -876,13 +892,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
    "name": "python",
-   "version": "3.12.0"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,