Fist comments added

d41fe38f · Patrick Scheidegger · c13943d0 · d41fe38f · d41fe38f · d41fe38f
Commit d41fe38f authored 2 years ago by Patrick Scheidegger
--- a/.gitignore
+++ b/.gitignore
 .DS_Store
+.ipynb_checkpoints/
\ No newline at end of file
--- a/.ipynb_checkpoints/Mini Project 1-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Mini Project 1-checkpoint.ipynb
 {
 "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e23f8e1",
+   "metadata": {},
+   "source": [
+    "# AI Applications Graded Miniproject 1: Deep Learning, multiclass image classification"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2161a24",
+   "metadata": {},
+   "source": [
+    "Team: Scheidegger, Patrick & Grob, Nils-Robin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4d9cfc22",
+   "metadata": {},
+   "source": [
+    "## Dataset\n",
+    "We chose following opensource [dataset](https://www.kaggle.com/datasets/alessiocorrado99/animals10) from alessiocorrado99.   \n",
+    "The dataset contains 10 classes of animals, namely dogs, cats, sheeps, elefants, horses, butterflies, chickens, and squirrels.    \n",
+    "There are approx. 25'000 images in the dataset."
+   ]
+  },
  {
   "cell_type": "code",
-   "execution_count": 5,
-   "id": "32009f57",
+   "execution_count": 2,
+   "id": "4f9c1d76",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting tensorflow\n",
+      "  Downloading tensorflow-2.11.0-cp310-cp310-win_amd64.whl (1.9 kB)\n",
+      "Collecting tensorflow-intel==2.11.0\n",
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+      "Collecting tensorflow-io-gcs-filesystem>=0.23.1\n",
+      "  Downloading tensorflow_io_gcs_filesystem-0.31.0-cp310-cp310-win_amd64.whl (1.5 MB)\n",
+      "     ---------------------------------------- 1.5/1.5 MB 47.6 MB/s eta 0:00:00\n",
+      "Collecting tensorflow-estimator<2.12,>=2.11.0\n",
+      "  Downloading tensorflow_estimator-2.11.0-py2.py3-none-any.whl (439 kB)\n",
+      "     ------------------------------------- 439.2/439.2 kB 28.6 MB/s eta 0:00:00\n",
+      "Collecting protobuf<3.20,>=3.9.2\n",
+      "  Downloading protobuf-3.19.6-cp310-cp310-win_amd64.whl (895 kB)\n",
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+      "Requirement already satisfied: packaging in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (21.3)\n",
+      "Collecting opt-einsum>=2.3.2\n",
+      "  Downloading opt_einsum-3.3.0-py3-none-any.whl (65 kB)\n",
+      "     ---------------------------------------- 65.5/65.5 kB ? eta 0:00:00\n",
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+      "  Downloading tensorboard-2.11.2-py3-none-any.whl (6.0 MB)\n",
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+      "Collecting flatbuffers>=2.0\n",
+      "  Downloading flatbuffers-23.1.21-py2.py3-none-any.whl (26 kB)\n",
+      "Collecting libclang>=13.0.0\n",
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+      "Collecting h5py>=2.9.0\n",
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+      "Requirement already satisfied: six>=1.12.0 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.16.0)\n",
+      "Collecting astunparse>=1.6.0\n",
+      "  Downloading astunparse-1.6.3-py2.py3-none-any.whl (12 kB)\n",
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+      "  Downloading google_pasta-0.2.0-py3-none-any.whl (57 kB)\n",
+      "     ---------------------------------------- 57.5/57.5 kB ? eta 0:00:00\n",
+      "Collecting keras<2.12,>=2.11.0\n",
+      "  Downloading keras-2.11.0-py2.py3-none-any.whl (1.7 MB)\n",
+      "     ---------------------------------------- 1.7/1.7 MB 54.0 MB/s eta 0:00:00\n",
+      "Collecting grpcio<2.0,>=1.24.3\n",
+      "  Downloading grpcio-1.51.3-cp310-cp310-win_amd64.whl (3.7 MB)\n",
+      "     ---------------------------------------- 3.7/3.7 MB 39.6 MB/s eta 0:00:00\n",
+      "Collecting wrapt>=1.11.0\n",
+      "  Downloading wrapt-1.15.0-cp310-cp310-win_amd64.whl (36 kB)\n",
+      "Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from astunparse>=1.6.0->tensorflow-intel==2.11.0->tensorflow) (0.37.1)\n",
+      "Collecting google-auth<3,>=1.6.3\n",
+      "  Downloading google_auth-2.16.1-py2.py3-none-any.whl (177 kB)\n",
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+      "Requirement already satisfied: requests<3,>=2.21.0 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.28.1)\n",
+      "Collecting tensorboard-data-server<0.7.0,>=0.6.0\n",
+      "  Downloading tensorboard_data_server-0.6.1-py3-none-any.whl (2.4 kB)\n",
+      "Collecting markdown>=2.6.8\n",
+      "  Downloading Markdown-3.4.1-py3-none-any.whl (93 kB)\n",
+      "     ---------------------------------------- 93.3/93.3 kB 5.2 MB/s eta 0:00:00\n",
+      "Collecting tensorboard-plugin-wit>=1.6.0\n",
+      "  Downloading tensorboard_plugin_wit-1.8.1-py3-none-any.whl (781 kB)\n",
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+      "Collecting google-auth-oauthlib<0.5,>=0.4.1\n",
+      "  Downloading google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB)\n",
+      "Collecting werkzeug>=1.0.1\n",
+      "  Downloading Werkzeug-2.2.3-py3-none-any.whl (233 kB)\n",
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+      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from packaging->tensorflow-intel==2.11.0->tensorflow) (3.0.9)\n",
+      "Collecting rsa<5,>=3.1.4\n",
+      "  Using cached rsa-4.9-py3-none-any.whl (34 kB)\n",
+      "Collecting pyasn1-modules>=0.2.1\n",
+      "  Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB)\n",
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+      "  Downloading cachetools-5.3.0-py3-none-any.whl (9.3 kB)\n",
+      "Collecting requests-oauthlib>=0.7.0\n",
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+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.26.11)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.4)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.9.24)\n",
+      "Requirement already satisfied: MarkupSafe>=2.1.1 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)\n",
+      "Collecting pyasn1<0.5.0,>=0.4.6\n",
+      "  Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)\n",
+      "Collecting oauthlib>=3.0.0\n",
+      "  Downloading oauthlib-3.2.2-py3-none-any.whl (151 kB)\n",
+      "     ---------------------------------------- 151.7/151.7 kB ? eta 0:00:00\n",
+      "Installing collected packages: tensorboard-plugin-wit, pyasn1, libclang, flatbuffers, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, rsa, pyasn1-modules, protobuf, opt-einsum, oauthlib, markdown, keras, h5py, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow\n",
+      "Successfully installed absl-py-1.4.0 astunparse-1.6.3 cachetools-5.3.0 flatbuffers-23.1.21 gast-0.4.0 google-auth-2.16.1 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.51.3 h5py-3.8.0 keras-2.11.0 libclang-15.0.6.1 markdown-3.4.1 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-3.19.6 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.11.2 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimator-2.11.0 tensorflow-intel-2.11.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.2.0 werkzeug-2.2.3 wrapt-1.15.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Pat\\miniconda3\\envs\\AIFO\\lib\\site-packages\\scipy\\__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.3\n",
+      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n"
+     ]
+    }
+   ],
   "source": [
-    "# Team\n",
-    "# AI Applications Mini Project 1\n",
-    "# Scheidegger, Patrick & Grob, Nils-Robin"
+    "!pip install tensorflow\n",
+    "import tensorflow as tf\n",
+    "\n",
+    "from tensorflow.keras import datasets, layers, models\n",
+    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "79549c17",
+   "id": "3b128ab4",
   "metadata": {},
   "outputs": [],
-   "source": [
-    "# Introduction\n",
-    "# Our dataset contains 10 classes: dogs, cats, sheeps, elefants, horse, butterfly, chicken, squirrel\n",
-    "# with about 25'000 images"
-   ]
+   "source": []
  },
  {
   "cell_type": "code",
@@ -292,7 +424,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.6"
  }
 },
 "nbformat": 4,

-%% Cell type:code id:32009f57 tags:
+%% Cell type:markdown id:1e23f8e1 tags:
+
+# AI Applications Graded Miniproject 1: Deep Learning, multiclass image classification
+
+%% Cell type:markdown id:d2161a24 tags:
+
+Team: Scheidegger, Patrick & Grob, Nils-Robin
+
+%% Cell type:markdown id:4d9cfc22 tags:
+
+## Dataset
+We chose following opensource [dataset](https://www.kaggle.com/datasets/alessiocorrado99/animals10) from alessiocorrado99.
+The dataset contains 10 classes of animals, namely dogs, cats, sheeps, elefants, horses, butterflies, chickens, and squirrels.
+There are approx. 25'000 images in the dataset.
+
+%% Cell type:code id:4f9c1d76 tags:

 ``` python
-# Team
-# AI Applications Mini Project 1
-# Scheidegger, Patrick & Grob, Nils-Robin
+!pip install tensorflow
+import tensorflow as tf
+
+from tensorflow.keras import datasets, layers, models
+import matplotlib.pyplot as plt
 ```

-%% Cell type:code id:79549c17 tags:
+%% Output
+
+    Collecting tensorflow
+      Downloading tensorflow-2.11.0-cp310-cp310-win_amd64.whl (1.9 kB)
+    Collecting tensorflow-intel==2.11.0
+      Downloading tensorflow_intel-2.11.0-cp310-cp310-win_amd64.whl (266.3 MB)
+         ------------------------------------- 266.3/266.3 MB 10.6 MB/s eta 0:00:00
+    Collecting tensorflow-io-gcs-filesystem>=0.23.1
+      Downloading tensorflow_io_gcs_filesystem-0.31.0-cp310-cp310-win_amd64.whl (1.5 MB)
+         ---------------------------------------- 1.5/1.5 MB 47.6 MB/s eta 0:00:00
+    Collecting tensorflow-estimator<2.12,>=2.11.0
+      Downloading tensorflow_estimator-2.11.0-py2.py3-none-any.whl (439 kB)
+         ------------------------------------- 439.2/439.2 kB 28.6 MB/s eta 0:00:00
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+    Requirement already satisfied: packaging in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (21.3)
+    Collecting opt-einsum>=2.3.2
+      Downloading opt_einsum-3.3.0-py3-none-any.whl (65 kB)
+         ---------------------------------------- 65.5/65.5 kB ? eta 0:00:00
+    Requirement already satisfied: setuptools in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (63.4.1)
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+      Downloading tensorboard-2.11.2-py3-none-any.whl (6.0 MB)
+         ---------------------------------------- 6.0/6.0 MB 34.8 MB/s eta 0:00:00
+    Collecting flatbuffers>=2.0
+      Downloading flatbuffers-23.1.21-py2.py3-none-any.whl (26 kB)
+    Collecting libclang>=13.0.0
+      Downloading libclang-15.0.6.1-py2.py3-none-win_amd64.whl (23.2 MB)
+         --------------------------------------- 23.2/23.2 MB 26.2 MB/s eta 0:00:00
+    Collecting h5py>=2.9.0
+      Downloading h5py-3.8.0-cp310-cp310-win_amd64.whl (2.6 MB)
+         ---------------------------------------- 2.6/2.6 MB 33.6 MB/s eta 0:00:00
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+    Collecting google-pasta>=0.1.1
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+         ---------------------------------------- 57.5/57.5 kB ? eta 0:00:00
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+      Downloading grpcio-1.51.3-cp310-cp310-win_amd64.whl (3.7 MB)
+         ---------------------------------------- 3.7/3.7 MB 39.6 MB/s eta 0:00:00
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+    Collecting rsa<5,>=3.1.4
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+    Collecting pyasn1<0.5.0,>=0.4.6
+      Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)
+    Collecting oauthlib>=3.0.0
+      Downloading oauthlib-3.2.2-py3-none-any.whl (151 kB)
+         ---------------------------------------- 151.7/151.7 kB ? eta 0:00:00
+    Installing collected packages: tensorboard-plugin-wit, pyasn1, libclang, flatbuffers, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, rsa, pyasn1-modules, protobuf, opt-einsum, oauthlib, markdown, keras, h5py, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow
+    Successfully installed absl-py-1.4.0 astunparse-1.6.3 cachetools-5.3.0 flatbuffers-23.1.21 gast-0.4.0 google-auth-2.16.1 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.51.3 h5py-3.8.0 keras-2.11.0 libclang-15.0.6.1 markdown-3.4.1 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-3.19.6 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.11.2 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimator-2.11.0 tensorflow-intel-2.11.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.2.0 werkzeug-2.2.3 wrapt-1.15.0
+
+    C:\Users\Pat\miniconda3\envs\AIFO\lib\site-packages\scipy\__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.3
+      warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion}"
+
+%% Cell type:code id:3b128ab4 tags:

 ``` python
-# Introduction
-# Our dataset contains 10 classes: dogs, cats, sheeps, elefants, horse, butterfly, chicken, squirrel
-# with about 25'000 images
 ```

 %% Cell type:code id:9237f546 tags:

 ``` python
 !pip install mplcyberpunk
 !pip install split-folders

 import cv2
 import matplotlib.pyplot as plt
 import pathlib, os, random, mplcyberpunk, math, splitfolders
 from keras.preprocessing.image import ImageDataGenerator
 import numpy as np
 import pandas as pd
 import tensorflow as tf
 from tensorflow.keras.layers import *
 from tensorflow.keras import Sequential
 ```

 %% Output

    Collecting mplcyberpunk
      Downloading mplcyberpunk-0.6.0-py3-none-any.whl (6.0 kB)
    Requirement already satisfied: matplotlib in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from mplcyberpunk) (3.5.2)
    Requirement already satisfied: packaging>=20.0 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (21.3)
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    Installing collected packages: mplcyberpunk
    Successfully installed mplcyberpunk-0.6.0
    Collecting split-folders
      Downloading split_folders-0.5.1-py3-none-any.whl (8.4 kB)
    Installing collected packages: split-folders
    Successfully installed split-folders-0.5.1

    ---------------------------------------------------------------------------
    ModuleNotFoundError                       Traceback (most recent call last)
 Input     In [6], in <cell line: 4>()
          1 get_ipython().system('pip install mplcyberpunk')
          2 get_ipython().system('pip install split-folders')
    ----> 4 import cv2
          5 import matplotlib.pyplot as plt
          6 import pathlib, os, random, mplcyberpunk, math, splitfolders
    ModuleNotFoundError: No module named 'cv2'

 %% Cell type:code id:6c8ea912 tags:

 ``` python
 epochs = 30
 batch_size = 32
 img_height, img_width = 400, 400
 input_shape = (img_height, img_width, 3)


 def create_data_sparse(data_bs):
    data_bs = pathlib.Path(data_bs)
    splitfolders.ratio(data_bs, output='Imgs/', seed=1234, ratio=(0.7, 0.15, 0.15), group_prefix=None)
    data_gen = ImageDataGenerator(rescale=1.0 / 255)
    train_ds = data_gen.flow_from_directory('Imgs/train/', target_size=(img_height, img_width),
                                            class_mode='sparse', batch_size=batch_size, subset='training')
    val_ds = data_gen.flow_from_directory('Imgs/val/', target_size=(img_height, img_width),
                                          class_mode='sparse', batch_size=batch_size, shuffle=False)

    return train_ds, val_ds

 train_ds, val_ds = create_data_sparse('/kaggle/input/animals10/raw-img/')
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [7], in <cell line: 18>()
         13     val_ds = data_gen.flow_from_directory('Imgs/val/', target_size=(img_height, img_width),
         14                                           class_mode='sparse', batch_size=batch_size, shuffle=False)
         16     return train_ds, val_ds
    ---> 18 train_ds, val_ds = create_data_sparse('/kaggle/input/animals10/raw-img/')
 Input     In [7], in create_data_sparse(data_bs)
          7 def create_data_sparse(data_bs):
    ----> 8     data_bs = pathlib.Path(data_bs)
          9     splitfolders.ratio(data_bs, output='Imgs/', seed=1234, ratio=(0.7, 0.15, 0.15), group_prefix=None)
         10     data_gen = ImageDataGenerator(rescale=1.0 / 255)
    NameError: name 'pathlib' is not defined

 %% Cell type:code id:b4710bff tags:

 ``` python
 class BaseModel(tf.keras.Model):
    def __init__(self):
        super(BaseModel, self).__init__()
        self.C1 = Conv2D(64, (3 * 3), padding='same', input_shape=input_shape)
        self.B1 = BatchNormalization()
        self.A1 = Activation('relu')
        self.P1 = MaxPooling2D(2, padding='same')

        self.C2 = Conv2D(32, (3 * 3), padding='same')
        self.B2 = BatchNormalization()
        self.A2 = Activation('relu')
        self.P2 = MaxPooling2D(2, padding='same')
        self.Dr1 = Dropout(0.2)

        self.C3 = Conv2D(32, (3 * 3), padding='same')
        self.B3 = BatchNormalization()
        self.A3 = Activation('relu')
        self.P3 = MaxPooling2D(2, padding='same')
        self.Dr2 = Dropout(0.3)

        self.F1 = Flatten()
        self.D1 = Dense(512, activation='relu')
        self.B4 = BatchNormalization()
        self.D2 = Dense(256, activation='relu')
        self.D3 = Dense(256, activation='relu')
        self.D4 = Dense(10, activation='softmax')


    def call(self, x):
        x = self.C1(x)
        x = self.B1(x)
        x = self.A1(x)
        x = self.P1(x)

        x = self.C2(x)
        x = self.B2(x)
        x = self.A2(x)
        x = self.P2(x)
        x = self.Dr1(x)

        x = self.C3(x)
        x = self.B3(x)
        x = self.A3(x)
        x = self.P3(x)
        x = self.Dr2(x)

        x = self.F1(x)
        x = self.D1(x)
        x = self.B4(x)
        x = self.D2(x)
        x = self.D3(x)
        y = self.D4(x)
        return y


    def __repr__(self):
        return 'Huang_Model'


 net = BaseModel()

 net.compile(optimizer='adam',
           loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
           metrics=['sparse_categorical_accuracy'])

 checkpoint_save_path = './BaseModel.ckpt'
 if os.path.exists(checkpoint_save_path + '.index'):
    net.load_weights(checkpoint_save_path)

 cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_save_path, save_weights_only=True, save_best_only=True)

 history = net.fit(train_ds, epochs=epochs, batch_size=batch_size, validation_data=val_ds, callbacks=[cp_callback])

 net.summary()

 file = open('./BaseModelWeights.txt', 'w')
 for v in net.trainable_variables:
    file.write(str(v.name) + '\n')
    file.write(str(v.shape) + '\n')
    file.write(str(v.numpy()) + '\n')

 file.close()
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [8], in <cell line: 1>()
    ----> 1 class BaseModel(tf.keras.Model):
          2     def __init__(self):
          3         super(BaseModel, self).__init__()
    NameError: name 'tf' is not defined

 %% Cell type:code id:80eb7f9d tags:

 ``` python
 acc = history.history['sparse_categorical_accuracy']
 val_acc = history.history['val_sparse_categorical_accuracy']
 loss = history.history['loss']
 val_loss = history.history['val_loss']

 plt.figure(figsize=(12, 6))
 plt.style.use('cyberpunk')
 plt.subplot(1, 2, 1)
 plt.plot(acc, label='Training Acc')
 plt.plot(val_acc, label='Validation Acc')
 plt.title('Training And Validation Acc')
 plt.legend()
 mplcyberpunk.add_glow_effects()


 plt.subplot(1, 2, 2)
 plt.plot(loss, label='Training Loss')
 plt.plot(val_loss, label='Validation Loss')
 plt.title('Training And Validation Loss')
 plt.legend()
 mplcyberpunk.add_glow_effects()
 plt.show()
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [9], in <cell line: 1>()
    ----> 1 acc = history.history['sparse_categorical_accuracy']
          2 val_acc = history.history['val_sparse_categorical_accuracy']
          3 loss = history.history['loss']
    NameError: name 'history' is not defined

 %% Cell type:code id:a19d17ff tags:

 ``` python
 ```

--- a/Mini Project 1.ipynb
+++ b/Mini Project 1.ipynb
 {
 "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e23f8e1",
+   "metadata": {},
+   "source": [
+    "# AI Applications Graded Miniproject 1: Deep Learning, multiclass image classification"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2161a24",
+   "metadata": {},
+   "source": [
+    "Team: Scheidegger, Patrick & Grob, Nils-Robin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4d9cfc22",
+   "metadata": {},
+   "source": [
+    "## Dataset\n",
+    "We chose following opensource [dataset](https://www.kaggle.com/datasets/alessiocorrado99/animals10) from alessiocorrado99.   \n",
+    "The dataset contains 10 classes of animals, namely dogs, cats, sheeps, elefants, horses, butterflies, chickens, and squirrels.    \n",
+    "There are approx. 25'000 images in the dataset."
+   ]
+  },
  {
   "cell_type": "code",
-   "execution_count": 5,
-   "id": "32009f57",
+   "execution_count": 2,
+   "id": "4f9c1d76",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting tensorflow\n",
+      "  Downloading tensorflow-2.11.0-cp310-cp310-win_amd64.whl (1.9 kB)\n",
+      "Collecting tensorflow-intel==2.11.0\n",
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+      "Collecting opt-einsum>=2.3.2\n",
+      "  Downloading opt_einsum-3.3.0-py3-none-any.whl (65 kB)\n",
+      "     ---------------------------------------- 65.5/65.5 kB ? eta 0:00:00\n",
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+      "  Downloading tensorboard-2.11.2-py3-none-any.whl (6.0 MB)\n",
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+      "  Downloading flatbuffers-23.1.21-py2.py3-none-any.whl (26 kB)\n",
+      "Collecting libclang>=13.0.0\n",
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+      "Collecting h5py>=2.9.0\n",
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+      "     ---------------------------------------- 2.6/2.6 MB 33.6 MB/s eta 0:00:00\n",
+      "Collecting termcolor>=1.1.0\n",
+      "  Downloading termcolor-2.2.0-py3-none-any.whl (6.6 kB)\n",
+      "Requirement already satisfied: typing-extensions>=3.6.6 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (4.3.0)\n",
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+      "  Downloading astunparse-1.6.3-py2.py3-none-any.whl (12 kB)\n",
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+      "     ---------------------------------------- 57.5/57.5 kB ? eta 0:00:00\n",
+      "Collecting keras<2.12,>=2.11.0\n",
+      "  Downloading keras-2.11.0-py2.py3-none-any.whl (1.7 MB)\n",
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+      "Collecting grpcio<2.0,>=1.24.3\n",
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+      "Collecting wrapt>=1.11.0\n",
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+      "Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from astunparse>=1.6.0->tensorflow-intel==2.11.0->tensorflow) (0.37.1)\n",
+      "Collecting google-auth<3,>=1.6.3\n",
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+      "Collecting tensorboard-data-server<0.7.0,>=0.6.0\n",
+      "  Downloading tensorboard_data_server-0.6.1-py3-none-any.whl (2.4 kB)\n",
+      "Collecting markdown>=2.6.8\n",
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+      "Collecting google-auth-oauthlib<0.5,>=0.4.1\n",
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+      "Collecting werkzeug>=1.0.1\n",
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+      "Collecting rsa<5,>=3.1.4\n",
+      "  Using cached rsa-4.9-py3-none-any.whl (34 kB)\n",
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+      "Collecting requests-oauthlib>=0.7.0\n",
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+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.26.11)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.4)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.9.24)\n",
+      "Requirement already satisfied: MarkupSafe>=2.1.1 in c:\\users\\pat\\miniconda3\\envs\\aifo\\lib\\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)\n",
+      "Collecting pyasn1<0.5.0,>=0.4.6\n",
+      "  Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)\n",
+      "Collecting oauthlib>=3.0.0\n",
+      "  Downloading oauthlib-3.2.2-py3-none-any.whl (151 kB)\n",
+      "     ---------------------------------------- 151.7/151.7 kB ? eta 0:00:00\n",
+      "Installing collected packages: tensorboard-plugin-wit, pyasn1, libclang, flatbuffers, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, rsa, pyasn1-modules, protobuf, opt-einsum, oauthlib, markdown, keras, h5py, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow\n",
+      "Successfully installed absl-py-1.4.0 astunparse-1.6.3 cachetools-5.3.0 flatbuffers-23.1.21 gast-0.4.0 google-auth-2.16.1 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.51.3 h5py-3.8.0 keras-2.11.0 libclang-15.0.6.1 markdown-3.4.1 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-3.19.6 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.11.2 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimator-2.11.0 tensorflow-intel-2.11.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.2.0 werkzeug-2.2.3 wrapt-1.15.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Pat\\miniconda3\\envs\\AIFO\\lib\\site-packages\\scipy\\__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.3\n",
+      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n"
+     ]
+    }
+   ],
   "source": [
-    "# Team\n",
-    "# AI Applications Mini Project 1\n",
-    "# Scheidegger, Patrick & Grob, Nils-Robin"
+    "!pip install tensorflow\n",
+    "import tensorflow as tf\n",
+    "\n",
+    "from tensorflow.keras import datasets, layers, models\n",
+    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
-   "id": "79549c17",
+   "id": "3b128ab4",
   "metadata": {},
   "outputs": [],
-   "source": [
-    "# Introduction\n",
-    "# Our dataset contains 10 classes: dogs, cats, sheeps, elefants, horse, butterfly, chicken, squirrel\n",
-    "# with about 25'000 images"
-   ]
+   "source": []
  },
  {
   "cell_type": "code",
@@ -292,7 +424,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.6"
  }
 },
 "nbformat": 4,

-%% Cell type:code id:32009f57 tags:
+%% Cell type:markdown id:1e23f8e1 tags:
+
+# AI Applications Graded Miniproject 1: Deep Learning, multiclass image classification
+
+%% Cell type:markdown id:d2161a24 tags:
+
+Team: Scheidegger, Patrick & Grob, Nils-Robin
+
+%% Cell type:markdown id:4d9cfc22 tags:
+
+## Dataset
+We chose following opensource [dataset](https://www.kaggle.com/datasets/alessiocorrado99/animals10) from alessiocorrado99.
+The dataset contains 10 classes of animals, namely dogs, cats, sheeps, elefants, horses, butterflies, chickens, and squirrels.
+There are approx. 25'000 images in the dataset.
+
+%% Cell type:code id:4f9c1d76 tags:

 ``` python
-# Team
-# AI Applications Mini Project 1
-# Scheidegger, Patrick & Grob, Nils-Robin
+!pip install tensorflow
+import tensorflow as tf
+
+from tensorflow.keras import datasets, layers, models
+import matplotlib.pyplot as plt
 ```

-%% Cell type:code id:79549c17 tags:
+%% Output
+
+    Collecting tensorflow
+      Downloading tensorflow-2.11.0-cp310-cp310-win_amd64.whl (1.9 kB)
+    Collecting tensorflow-intel==2.11.0
+      Downloading tensorflow_intel-2.11.0-cp310-cp310-win_amd64.whl (266.3 MB)
+         ------------------------------------- 266.3/266.3 MB 10.6 MB/s eta 0:00:00
+    Collecting tensorflow-io-gcs-filesystem>=0.23.1
+      Downloading tensorflow_io_gcs_filesystem-0.31.0-cp310-cp310-win_amd64.whl (1.5 MB)
+         ---------------------------------------- 1.5/1.5 MB 47.6 MB/s eta 0:00:00
+    Collecting tensorflow-estimator<2.12,>=2.11.0
+      Downloading tensorflow_estimator-2.11.0-py2.py3-none-any.whl (439 kB)
+         ------------------------------------- 439.2/439.2 kB 28.6 MB/s eta 0:00:00
+    Collecting protobuf<3.20,>=3.9.2
+      Downloading protobuf-3.19.6-cp310-cp310-win_amd64.whl (895 kB)
+         ------------------------------------- 895.7/895.7 kB 55.3 MB/s eta 0:00:00
+    Requirement already satisfied: packaging in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (21.3)
+    Collecting opt-einsum>=2.3.2
+      Downloading opt_einsum-3.3.0-py3-none-any.whl (65 kB)
+         ---------------------------------------- 65.5/65.5 kB ? eta 0:00:00
+    Requirement already satisfied: setuptools in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (63.4.1)
+    Collecting tensorboard<2.12,>=2.11
+      Downloading tensorboard-2.11.2-py3-none-any.whl (6.0 MB)
+         ---------------------------------------- 6.0/6.0 MB 34.8 MB/s eta 0:00:00
+    Collecting flatbuffers>=2.0
+      Downloading flatbuffers-23.1.21-py2.py3-none-any.whl (26 kB)
+    Collecting libclang>=13.0.0
+      Downloading libclang-15.0.6.1-py2.py3-none-win_amd64.whl (23.2 MB)
+         --------------------------------------- 23.2/23.2 MB 26.2 MB/s eta 0:00:00
+    Collecting h5py>=2.9.0
+      Downloading h5py-3.8.0-cp310-cp310-win_amd64.whl (2.6 MB)
+         ---------------------------------------- 2.6/2.6 MB 33.6 MB/s eta 0:00:00
+    Collecting termcolor>=1.1.0
+      Downloading termcolor-2.2.0-py3-none-any.whl (6.6 kB)
+    Requirement already satisfied: typing-extensions>=3.6.6 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (4.3.0)
+    Collecting absl-py>=1.0.0
+      Downloading absl_py-1.4.0-py3-none-any.whl (126 kB)
+         -------------------------------------- 126.5/126.5 kB 7.3 MB/s eta 0:00:00
+    Requirement already satisfied: numpy>=1.20 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.23.3)
+    Requirement already satisfied: six>=1.12.0 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.16.0)
+    Collecting astunparse>=1.6.0
+      Downloading astunparse-1.6.3-py2.py3-none-any.whl (12 kB)
+    Collecting gast<=0.4.0,>=0.2.1
+      Downloading gast-0.4.0-py3-none-any.whl (9.8 kB)
+    Collecting google-pasta>=0.1.1
+      Downloading google_pasta-0.2.0-py3-none-any.whl (57 kB)
+         ---------------------------------------- 57.5/57.5 kB ? eta 0:00:00
+    Collecting keras<2.12,>=2.11.0
+      Downloading keras-2.11.0-py2.py3-none-any.whl (1.7 MB)
+         ---------------------------------------- 1.7/1.7 MB 54.0 MB/s eta 0:00:00
+    Collecting grpcio<2.0,>=1.24.3
+      Downloading grpcio-1.51.3-cp310-cp310-win_amd64.whl (3.7 MB)
+         ---------------------------------------- 3.7/3.7 MB 39.6 MB/s eta 0:00:00
+    Collecting wrapt>=1.11.0
+      Downloading wrapt-1.15.0-cp310-cp310-win_amd64.whl (36 kB)
+    Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from astunparse>=1.6.0->tensorflow-intel==2.11.0->tensorflow) (0.37.1)
+    Collecting google-auth<3,>=1.6.3
+      Downloading google_auth-2.16.1-py2.py3-none-any.whl (177 kB)
+         ------------------------------------- 177.2/177.2 kB 10.4 MB/s eta 0:00:00
+    Requirement already satisfied: requests<3,>=2.21.0 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.28.1)
+    Collecting tensorboard-data-server<0.7.0,>=0.6.0
+      Downloading tensorboard_data_server-0.6.1-py3-none-any.whl (2.4 kB)
+    Collecting markdown>=2.6.8
+      Downloading Markdown-3.4.1-py3-none-any.whl (93 kB)
+         ---------------------------------------- 93.3/93.3 kB 5.2 MB/s eta 0:00:00
+    Collecting tensorboard-plugin-wit>=1.6.0
+      Downloading tensorboard_plugin_wit-1.8.1-py3-none-any.whl (781 kB)
+         ------------------------------------- 781.3/781.3 kB 51.4 MB/s eta 0:00:00
+    Collecting google-auth-oauthlib<0.5,>=0.4.1
+      Downloading google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB)
+    Collecting werkzeug>=1.0.1
+      Downloading Werkzeug-2.2.3-py3-none-any.whl (233 kB)
+         ------------------------------------- 233.6/233.6 kB 14.0 MB/s eta 0:00:00
+    Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from packaging->tensorflow-intel==2.11.0->tensorflow) (3.0.9)
+    Collecting rsa<5,>=3.1.4
+      Using cached rsa-4.9-py3-none-any.whl (34 kB)
+    Collecting pyasn1-modules>=0.2.1
+      Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB)
+    Collecting cachetools<6.0,>=2.0.0
+      Downloading cachetools-5.3.0-py3-none-any.whl (9.3 kB)
+    Collecting requests-oauthlib>=0.7.0
+      Downloading requests_oauthlib-1.3.1-py2.py3-none-any.whl (23 kB)
+    Requirement already satisfied: charset-normalizer<3,>=2 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.0.4)
+    Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.26.11)
+    Requirement already satisfied: idna<4,>=2.5 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.4)
+    Requirement already satisfied: certifi>=2017.4.17 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.9.24)
+    Requirement already satisfied: MarkupSafe>=2.1.1 in c:\users\pat\miniconda3\envs\aifo\lib\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)
+    Collecting pyasn1<0.5.0,>=0.4.6
+      Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)
+    Collecting oauthlib>=3.0.0
+      Downloading oauthlib-3.2.2-py3-none-any.whl (151 kB)
+         ---------------------------------------- 151.7/151.7 kB ? eta 0:00:00
+    Installing collected packages: tensorboard-plugin-wit, pyasn1, libclang, flatbuffers, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, rsa, pyasn1-modules, protobuf, opt-einsum, oauthlib, markdown, keras, h5py, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow
+    Successfully installed absl-py-1.4.0 astunparse-1.6.3 cachetools-5.3.0 flatbuffers-23.1.21 gast-0.4.0 google-auth-2.16.1 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.51.3 h5py-3.8.0 keras-2.11.0 libclang-15.0.6.1 markdown-3.4.1 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-3.19.6 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.11.2 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimator-2.11.0 tensorflow-intel-2.11.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.2.0 werkzeug-2.2.3 wrapt-1.15.0
+
+    C:\Users\Pat\miniconda3\envs\AIFO\lib\site-packages\scipy\__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.3
+      warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion}"
+
+%% Cell type:code id:3b128ab4 tags:

 ``` python
-# Introduction
-# Our dataset contains 10 classes: dogs, cats, sheeps, elefants, horse, butterfly, chicken, squirrel
-# with about 25'000 images
 ```

 %% Cell type:code id:9237f546 tags:

 ``` python
 !pip install mplcyberpunk
 !pip install split-folders

 import cv2
 import matplotlib.pyplot as plt
 import pathlib, os, random, mplcyberpunk, math, splitfolders
 from keras.preprocessing.image import ImageDataGenerator
 import numpy as np
 import pandas as pd
 import tensorflow as tf
 from tensorflow.keras.layers import *
 from tensorflow.keras import Sequential
 ```

 %% Output

    Collecting mplcyberpunk
      Downloading mplcyberpunk-0.6.0-py3-none-any.whl (6.0 kB)
    Requirement already satisfied: matplotlib in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from mplcyberpunk) (3.5.2)
    Requirement already satisfied: packaging>=20.0 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (21.3)
    Requirement already satisfied: fonttools>=4.22.0 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (4.25.0)
    Requirement already satisfied: python-dateutil>=2.7 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (2.8.2)
    Requirement already satisfied: pillow>=6.2.0 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (9.2.0)
    Requirement already satisfied: numpy>=1.17 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (1.23.3)
    Requirement already satisfied: cycler>=0.10 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (0.11.0)
    Requirement already satisfied: kiwisolver>=1.0.1 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (1.4.2)
    Requirement already satisfied: pyparsing>=2.2.1 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from matplotlib->mplcyberpunk) (3.0.9)
    Requirement already satisfied: six>=1.5 in /Users/nilsrobingrob/miniconda3/envs/AIFO/lib/python3.9/site-packages (from python-dateutil>=2.7->matplotlib->mplcyberpunk) (1.16.0)
    Installing collected packages: mplcyberpunk
    Successfully installed mplcyberpunk-0.6.0
    Collecting split-folders
      Downloading split_folders-0.5.1-py3-none-any.whl (8.4 kB)
    Installing collected packages: split-folders
    Successfully installed split-folders-0.5.1

    ---------------------------------------------------------------------------
    ModuleNotFoundError                       Traceback (most recent call last)
 Input     In [6], in <cell line: 4>()
          1 get_ipython().system('pip install mplcyberpunk')
          2 get_ipython().system('pip install split-folders')
    ----> 4 import cv2
          5 import matplotlib.pyplot as plt
          6 import pathlib, os, random, mplcyberpunk, math, splitfolders
    ModuleNotFoundError: No module named 'cv2'

 %% Cell type:code id:6c8ea912 tags:

 ``` python
 epochs = 30
 batch_size = 32
 img_height, img_width = 400, 400
 input_shape = (img_height, img_width, 3)


 def create_data_sparse(data_bs):
    data_bs = pathlib.Path(data_bs)
    splitfolders.ratio(data_bs, output='Imgs/', seed=1234, ratio=(0.7, 0.15, 0.15), group_prefix=None)
    data_gen = ImageDataGenerator(rescale=1.0 / 255)
    train_ds = data_gen.flow_from_directory('Imgs/train/', target_size=(img_height, img_width),
                                            class_mode='sparse', batch_size=batch_size, subset='training')
    val_ds = data_gen.flow_from_directory('Imgs/val/', target_size=(img_height, img_width),
                                          class_mode='sparse', batch_size=batch_size, shuffle=False)

    return train_ds, val_ds

 train_ds, val_ds = create_data_sparse('/kaggle/input/animals10/raw-img/')
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [7], in <cell line: 18>()
         13     val_ds = data_gen.flow_from_directory('Imgs/val/', target_size=(img_height, img_width),
         14                                           class_mode='sparse', batch_size=batch_size, shuffle=False)
         16     return train_ds, val_ds
    ---> 18 train_ds, val_ds = create_data_sparse('/kaggle/input/animals10/raw-img/')
 Input     In [7], in create_data_sparse(data_bs)
          7 def create_data_sparse(data_bs):
    ----> 8     data_bs = pathlib.Path(data_bs)
          9     splitfolders.ratio(data_bs, output='Imgs/', seed=1234, ratio=(0.7, 0.15, 0.15), group_prefix=None)
         10     data_gen = ImageDataGenerator(rescale=1.0 / 255)
    NameError: name 'pathlib' is not defined

 %% Cell type:code id:b4710bff tags:

 ``` python
 class BaseModel(tf.keras.Model):
    def __init__(self):
        super(BaseModel, self).__init__()
        self.C1 = Conv2D(64, (3 * 3), padding='same', input_shape=input_shape)
        self.B1 = BatchNormalization()
        self.A1 = Activation('relu')
        self.P1 = MaxPooling2D(2, padding='same')

        self.C2 = Conv2D(32, (3 * 3), padding='same')
        self.B2 = BatchNormalization()
        self.A2 = Activation('relu')
        self.P2 = MaxPooling2D(2, padding='same')
        self.Dr1 = Dropout(0.2)

        self.C3 = Conv2D(32, (3 * 3), padding='same')
        self.B3 = BatchNormalization()
        self.A3 = Activation('relu')
        self.P3 = MaxPooling2D(2, padding='same')
        self.Dr2 = Dropout(0.3)

        self.F1 = Flatten()
        self.D1 = Dense(512, activation='relu')
        self.B4 = BatchNormalization()
        self.D2 = Dense(256, activation='relu')
        self.D3 = Dense(256, activation='relu')
        self.D4 = Dense(10, activation='softmax')


    def call(self, x):
        x = self.C1(x)
        x = self.B1(x)
        x = self.A1(x)
        x = self.P1(x)

        x = self.C2(x)
        x = self.B2(x)
        x = self.A2(x)
        x = self.P2(x)
        x = self.Dr1(x)

        x = self.C3(x)
        x = self.B3(x)
        x = self.A3(x)
        x = self.P3(x)
        x = self.Dr2(x)

        x = self.F1(x)
        x = self.D1(x)
        x = self.B4(x)
        x = self.D2(x)
        x = self.D3(x)
        y = self.D4(x)
        return y


    def __repr__(self):
        return 'Huang_Model'


 net = BaseModel()

 net.compile(optimizer='adam',
           loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
           metrics=['sparse_categorical_accuracy'])

 checkpoint_save_path = './BaseModel.ckpt'
 if os.path.exists(checkpoint_save_path + '.index'):
    net.load_weights(checkpoint_save_path)

 cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_save_path, save_weights_only=True, save_best_only=True)

 history = net.fit(train_ds, epochs=epochs, batch_size=batch_size, validation_data=val_ds, callbacks=[cp_callback])

 net.summary()

 file = open('./BaseModelWeights.txt', 'w')
 for v in net.trainable_variables:
    file.write(str(v.name) + '\n')
    file.write(str(v.shape) + '\n')
    file.write(str(v.numpy()) + '\n')

 file.close()
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [8], in <cell line: 1>()
    ----> 1 class BaseModel(tf.keras.Model):
          2     def __init__(self):
          3         super(BaseModel, self).__init__()
    NameError: name 'tf' is not defined

 %% Cell type:code id:80eb7f9d tags:

 ``` python
 acc = history.history['sparse_categorical_accuracy']
 val_acc = history.history['val_sparse_categorical_accuracy']
 loss = history.history['loss']
 val_loss = history.history['val_loss']

 plt.figure(figsize=(12, 6))
 plt.style.use('cyberpunk')
 plt.subplot(1, 2, 1)
 plt.plot(acc, label='Training Acc')
 plt.plot(val_acc, label='Validation Acc')
 plt.title('Training And Validation Acc')
 plt.legend()
 mplcyberpunk.add_glow_effects()


 plt.subplot(1, 2, 2)
 plt.plot(loss, label='Training Loss')
 plt.plot(val_loss, label='Validation Loss')
 plt.title('Training And Validation Loss')
 plt.legend()
 mplcyberpunk.add_glow_effects()
 plt.show()
 ```

 %% Output

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
 Input     In [9], in <cell line: 1>()
    ----> 1 acc = history.history['sparse_categorical_accuracy']
          2 val_acc = history.history['val_sparse_categorical_accuracy']
          3 loss = history.history['loss']
    NameError: name 'history' is not defined

 %% Cell type:code id:a19d17ff tags:

 ``` python
 ```