{"id":146664,"date":"2025-08-22T12:20:18","date_gmt":"2025-08-22T06:50:18","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=146664"},"modified":"2025-08-22T12:20:18","modified_gmt":"2025-08-22T06:50:18","slug":"image-classification-of-fashion-items-using-ann","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/","title":{"rendered":"Deep Learning Project &#8211; Image Classification of Fashion Items using ANN"},"content":{"rendered":"<h3>Program 1<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">Classifying Clothing Images Using Artificial Neural Network (ANN)\r\nWe want create a model which teach a machine to look at a small grayscale image of a fashion item (like a T-shirt or sneaker) and guess what it is.\r\n# Built-in dataset in Keras (no need to download separately).\r\n# Each image is 28 \u00d7 28 pixels (black &amp; white).\r\n# Each image shows one clothing item.\r\n# There are 10 categories (T-shirt\/top, trouser, dress, etc.)\r\n\r\n\r\n# 1. Import libraries\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom tensorflow.keras.datasets import fashion_mnist\r\nfrom tensorflow.keras.models import Sequential\r\nfrom tensorflow.keras.layers import Dense, Flatten\r\nfrom tensorflow.keras.utils import to_categorical\r\nfrom sklearn.metrics import classification_report, confusion_matrix\r\nimport seaborn as sns\r\n\r\n# 2. Load Fashion MNIST data\r\n# X_train: 60,000 training images\r\n# y_train: their correct labels\r\n# X_test: 10,000 test images\r\n# y_test: their labels\r\n\r\n(X_train, y_train), (X_test, y_test) = fashion_mnist.load_data()\r\n\r\n\r\n# 3. Normalize pixel values (0 to 1)\r\n# Each pixel value is between 0 and 255.\r\n# We scale them to 0\u20131 range, which makes training easier.\r\n\r\nX_train = X_train \/ 255.0\r\nX_test = X_test \/ 255.0\r\n\r\n# 4. Convert labels to one-hot vectors\r\n# Instead of labels like 5 or 9, we convert them to vectors like:\r\n# Label 3 \u2192 [0, 0, 0, 1, 0, 0, 0, 0, 0, 0]\r\n# This is needed for multi-class classification.\r\n\r\ny_train_cat = to_categorical(y_train, num_classes=10)\r\ny_test_cat = to_categorical(y_test, num_classes=10)\r\n\r\n# 5. Build ANN model\r\n# Flatten: Converts 28\u00d728 image into a long row (784 pixels).\r\n# Dense(128): First layer with 128 neurons \u2192 learns patterns.\r\n# Dense(64): Second layer with 64 neurons \u2192 deeper learning.\r\n# Dense(10): Output layer with 10 neurons (for 10 classes).\r\n# softmax helps pick the best class.\r\n\r\nmodel = Sequential([\r\n    Flatten(input_shape=(28, 28)),          # Converts 28x28 image to 784 vector\r\n    Dense(128, activation='relu'),\r\n    Dense(64, activation='relu'),\r\n    Dense(10, activation='softmax')         # 10 categories = 10 output neurons\r\n])\r\n\r\n# 6. Compile model\r\n# Adam: Optimizer that adjusts the model weights.\r\n# Loss: We want to minimize this during training.\r\n# Accuracy: Our performance metric.\r\n\r\nmodel.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])\r\n\r\n# 7. Train model\r\n# Trains the model using training data.\r\n# 10 epochs: Train the full data 10 times.\r\n# batch_size=128: Use 128 images at a time.\r\n# validation_split=0.1: Keep 10% of training data for validation.\r\n\r\nhistory = model.fit(X_train, y_train_cat, epochs=10, batch_size=128, validation_split=0.1)\r\n\r\n# 8. Evaluate model\r\n# We now test how well our model performs on unseen data\r\nloss, acc = model.evaluate(X_test, y_test_cat)\r\nprint(f\"\\nTest Accuracy: {acc*100:.2f}%\")\r\n\r\n# 9. Predict on test set\r\n# Predict the class probabilities for each image.\r\n# Convert probabilities to actual class label (e.g., 0\u20139).\r\n\r\ny_pred_probs = model.predict(X_test)\r\ny_pred = np.argmax(y_pred_probs, axis=1)\r\ny_pred\r\n\r\n# 10. Classification Report\r\n# Precision,Recall,F1-score----&gt; for each of the 10 clothing classes.\r\n\r\nprint(\"\\nClassification Report:\")\r\nprint(classification_report(y_test, y_pred))\r\n\r\n# 11. Confusion Matrix\r\ncm = confusion_matrix(y_test, y_pred)\r\nplt.figure(figsize=(8,6))\r\nsns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\")\r\nplt.title(\"Confusion Matrix\")\r\nplt.xlabel(\"Predicted\")\r\nplt.ylabel(\"Actual\")\r\nplt.show()\r\n\r\n# 12. Display 10 sample predictions\r\nclass_names = ['T-shirt', 'Trouser', 'Pullover', 'Dress', 'Coat',\r\n               'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']\r\n\r\nplt.figure(figsize=(12,4))\r\nfor i in range(10):\r\n    plt.subplot(2, 5, i+1)\r\n    plt.imshow(X_test[i], cmap='gray')\r\n    plt.title(f\"Actual: {class_names[y_test[i]]}\\nPred: {class_names[y_pred[i]]}\")\r\n    plt.axis('off')\r\nplt.tight_layout()\r\nplt.show()<\/pre>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 Classifying Clothing Images Using Artificial Neural Network (ANN) We want create a model which teach a machine to look at a small grayscale image of a fashion item (like a T-shirt or&#46;&#46;&#46;<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[35122,35123,35124,35125,8431,33127,33128,20697],"class_list":["post-146664","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-image-classification-of-fashion-items","tag-image-classification-of-fashion-items-using-ann","tag-image-classification-of-fashion-items-using-deep-learning","tag-image-classification-of-fashion-items-using-machine-learning","tag-machine-learning","tag-machine-learning-practical","tag-machine-learning-program","tag-machine-learning-project"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Deep Learning Project - Image Classification of Fashion Items using ANN - DataFlair<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deep Learning Project - Image Classification of Fashion Items using ANN - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Program 1 Classifying Clothing Images Using Artificial Neural Network (ANN) We want create a model which teach a machine to look at a small grayscale image of a fashion item (like a T-shirt or&#046;&#046;&#046;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-22T06:50:18+00:00\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Deep Learning Project - Image Classification of Fashion Items using ANN - DataFlair","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/","og_locale":"en_US","og_type":"article","og_title":"Deep Learning Project - Image Classification of Fashion Items using ANN - DataFlair","og_description":"Program 1 Classifying Clothing Images Using Artificial Neural Network (ANN) We want create a model which teach a machine to look at a small grayscale image of a fashion item (like a T-shirt or&#46;&#46;&#46;","og_url":"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-08-22T06:50:18+00:00","author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/image-classification-of-fashion-items-using-ann\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"Deep Learning Project &#8211; 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