Update post titles and descriptions; enhance image links and add link…

… switching functionality

_notebooks/2024-09-10-fruits.ipynb

@@ -28,15 +28,15 @@
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "2024-09-10 15:03:36.561488: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
-            "2024-09-10 15:03:36.572677: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
-            "2024-09-10 15:03:36.585013: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
-            "2024-09-10 15:03:36.592131: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
-            "2024-09-10 15:03:36.604797: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
-            "2024-09-10 15:03:36.608159: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
-            "2024-09-10 15:03:36.623869: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+            "2024-09-11 15:18:48.720257: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+            "2024-09-11 15:18:48.720757: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
+            "2024-09-11 15:18:48.733149: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
+            "2024-09-11 15:18:48.749215: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "2024-09-11 15:18:48.767948: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "2024-09-11 15:18:48.774441: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "2024-09-11 15:18:48.796444: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
             "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
-            "2024-09-10 15:03:38.089379: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+            "2024-09-11 15:18:50.268827: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
           ]
         }
       ],

_site/assets/js/search-data.json

@@ -2,8 +2,8 @@
 
 
         "post0": {
-            "title": "Fruits",
-            "content": "print("Hello World") . Hello World .",
+            "title": "hello",
+            "content": "import emoji print(emoji.emojize("Hello, World! :red_heart:")) . Hello, World! ❤️ .",
             "url": "http://localhost:4100/adi_student/posts/hello",
             "relUrl": "/posts/hello",
             "date": " • Sep 11, 2024"
@@ -14,7 +14,7 @@
 
         ,"post1": {
             "title": "Fruits",
-            "content": "import tensorflow as tf from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout from tensorflow.keras.optimizers import Adam . 2024-09-10 15:03:36.561488: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. 2024-09-10 15:03:36.572677: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used. 2024-09-10 15:03:36.585013: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used. 2024-09-10 15:03:36.592131: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2024-09-10 15:03:36.604797: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2024-09-10 15:03:36.608159: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2024-09-10 15:03:36.623869: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. 2024-09-10 15:03:38.089379: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT . # Define paths train_dir = r'Documents kaggle fruits360 fruits-360_dataset fruits-360 Training' test_dir = r'Documents kaggle fruits360 fruits-360_dataset fruits-360 Test' . # Image data generators for loading and augmenting the images train_datagen = ImageDataGenerator( rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True ) test_datagen = ImageDataGenerator(rescale=1./255) train_generator = train_datagen.flow_from_directory( train_dir, target_size=(100, 100), batch_size=32, class_mode='categorical' ) test_generator = test_datagen.flow_from_directory( test_dir, target_size=(100, 100), batch_size=32, class_mode='categorical' ) . FileNotFoundError Traceback (most recent call last) Cell In[3], line 11 2 train_datagen = ImageDataGenerator( 3 rescale=1./255, 4 shear_range=0.2, 5 zoom_range=0.2, 6 horizontal_flip=True 7 ) 9 test_datagen = ImageDataGenerator(rescale=1./255) > 11 train_generator = train_datagen.flow_from_directory( 12 train_dir, 13 target_size=(100, 100), 14 batch_size=32, 15 class_mode='categorical' 16 ) 18 test_generator = test_datagen.flow_from_directory( 19 test_dir, 20 target_size=(100, 100), 21 batch_size=32, 22 class_mode='categorical' 23 ) File ~/adi_student/venv/lib/python3.10/site-packages/keras/src/legacy/preprocessing/image.py:1138, in ImageDataGenerator.flow_from_directory(self, directory, target_size, color_mode, classes, class_mode, batch_size, shuffle, seed, save_to_dir, save_prefix, save_format, follow_links, subset, interpolation, keep_aspect_ratio) 1120 def flow_from_directory( 1121 self, 1122 directory, (...) 1136 keep_aspect_ratio=False, 1137 ): -> 1138 return DirectoryIterator( 1139 directory, 1140 self, 1141 target_size=target_size, 1142 color_mode=color_mode, 1143 keep_aspect_ratio=keep_aspect_ratio, 1144 classes=classes, 1145 class_mode=class_mode, 1146 data_format=self.data_format, 1147 batch_size=batch_size, 1148 shuffle=shuffle, 1149 seed=seed, 1150 save_to_dir=save_to_dir, 1151 save_prefix=save_prefix, 1152 save_format=save_format, 1153 follow_links=follow_links, 1154 subset=subset, 1155 interpolation=interpolation, 1156 dtype=self.dtype, 1157 ) File ~/adi_student/venv/lib/python3.10/site-packages/keras/src/legacy/preprocessing/image.py:453, in DirectoryIterator.__init__(self, directory, image_data_generator, target_size, color_mode, classes, class_mode, batch_size, shuffle, seed, data_format, save_to_dir, save_prefix, save_format, follow_links, subset, interpolation, keep_aspect_ratio, dtype) 451 if not classes: 452 classes = [] --> 453 for subdir in sorted(os.listdir(directory)): 454 if os.path.isdir(os.path.join(directory, subdir)): 455 classes.append(subdir) FileNotFoundError: [Errno 2] No such file or directory: 'Documents kaggle fruits360 fruits-360_dataset fruits-360 Training' . # Building the CNN model model = Sequential([ Conv2D(32, (3, 3), activation='relu', input_shape=(100, 100, 3)), MaxPooling2D(pool_size=(2, 2)), Conv2D(64, (3, 3), activation='relu'), MaxPooling2D(pool_size=(2, 2)), Conv2D(128, (3, 3), activation='relu'), MaxPooling2D(pool_size=(2, 2)), Flatten(), Dense(512, activation='relu'), Dropout(0.5), Dense(131, activation='softmax') # 131 classes in the dataset ]) # Compile the model model.compile(optimizer=Adam(), loss='categorical_crossentropy', metrics=['accuracy']) . # Determine steps per epoch and validation steps steps_per_epoch = train_generator.samples // train_generator.batch_size validation_steps = test_generator.samples // test_generator.batch_size . # Evaluate the model loss, accuracy = model.evaluate(test_generator) print(f'Test accuracy: {accuracy * 100:.2f}%') . Found 67692 images belonging to 131 classes. Found 22688 images belonging to 131 classes. C: Users adity AppData Local Programs Python Python312 Lib site-packages keras src layers convolutional base_conv.py:107: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead. super().__init__(activity_regularizer=activity_regularizer, **kwargs) Epoch 1/15 C: Users adity AppData Local Programs Python Python312 Lib site-packages keras src trainers data_adapters py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored. self._warn_if_super_not_called() 2115/2115 ━━━━━━━━━━━━━━━━━━━━ 720s 338ms/step - accuracy: 0.4970 - loss: 1.9714 - val_accuracy: 0.9128 - val_loss: 0.3601 Epoch 2/15  1/2115 ━━━━━━━━━━━━━━━━━━━━ 6:14 177ms/step - accuracy: 0.8750 - loss: 0.2425 C: Users adity AppData Local Programs Python Python312 Lib contextlib.py:158: UserWarning: Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches. You may need to use the `.repeat()` function when building your dataset. self.gen.throw(value) An error occurred: 'NoneType' object has no attribute 'items' 709/709 ━━━━━━━━━━━━━━━━━━━━ 46s 65ms/step - accuracy: 0.9185 - loss: 0.3224 Test accuracy: 91.70% .",
+            "content": "import tensorflow as tf from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout from tensorflow.keras.optimizers import Adam . 2024-09-11 15:18:48.720257: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. 2024-09-11 15:18:48.720757: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used. 2024-09-11 15:18:48.733149: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used. 2024-09-11 15:18:48.749215: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2024-09-11 15:18:48.767948: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2024-09-11 15:18:48.774441: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2024-09-11 15:18:48.796444: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. 2024-09-11 15:18:50.268827: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT . # Define paths train_dir = r'Documents kaggle fruits360 fruits-360_dataset fruits-360 Training' test_dir = r'Documents kaggle fruits360 fruits-360_dataset fruits-360 Test' . # Image data generators for loading and augmenting the images train_datagen = ImageDataGenerator( rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True ) test_datagen = ImageDataGenerator(rescale=1./255) train_generator = train_datagen.flow_from_directory( train_dir, target_size=(100, 100), batch_size=32, class_mode='categorical' ) test_generator = test_datagen.flow_from_directory( test_dir, target_size=(100, 100), batch_size=32, class_mode='categorical' ) . FileNotFoundError Traceback (most recent call last) Cell In[3], line 11 2 train_datagen = ImageDataGenerator( 3 rescale=1./255, 4 shear_range=0.2, 5 zoom_range=0.2, 6 horizontal_flip=True 7 ) 9 test_datagen = ImageDataGenerator(rescale=1./255) > 11 train_generator = train_datagen.flow_from_directory( 12 train_dir, 13 target_size=(100, 100), 14 batch_size=32, 15 class_mode='categorical' 16 ) 18 test_generator = test_datagen.flow_from_directory( 19 test_dir, 20 target_size=(100, 100), 21 batch_size=32, 22 class_mode='categorical' 23 ) File ~/adi_student/venv/lib/python3.10/site-packages/keras/src/legacy/preprocessing/image.py:1138, in ImageDataGenerator.flow_from_directory(self, directory, target_size, color_mode, classes, class_mode, batch_size, shuffle, seed, save_to_dir, save_prefix, save_format, follow_links, subset, interpolation, keep_aspect_ratio) 1120 def flow_from_directory( 1121 self, 1122 directory, (...) 1136 keep_aspect_ratio=False, 1137 ): -> 1138 return DirectoryIterator( 1139 directory, 1140 self, 1141 target_size=target_size, 1142 color_mode=color_mode, 1143 keep_aspect_ratio=keep_aspect_ratio, 1144 classes=classes, 1145 class_mode=class_mode, 1146 data_format=self.data_format, 1147 batch_size=batch_size, 1148 shuffle=shuffle, 1149 seed=seed, 1150 save_to_dir=save_to_dir, 1151 save_prefix=save_prefix, 1152 save_format=save_format, 1153 follow_links=follow_links, 1154 subset=subset, 1155 interpolation=interpolation, 1156 dtype=self.dtype, 1157 ) File ~/adi_student/venv/lib/python3.10/site-packages/keras/src/legacy/preprocessing/image.py:453, in DirectoryIterator.__init__(self, directory, image_data_generator, target_size, color_mode, classes, class_mode, batch_size, shuffle, seed, data_format, save_to_dir, save_prefix, save_format, follow_links, subset, interpolation, keep_aspect_ratio, dtype) 451 if not classes: 452 classes = [] --> 453 for subdir in sorted(os.listdir(directory)): 454 if os.path.isdir(os.path.join(directory, subdir)): 455 classes.append(subdir) FileNotFoundError: [Errno 2] No such file or directory: 'Documents kaggle fruits360 fruits-360_dataset fruits-360 Training' . # Building the CNN model model = Sequential([ Conv2D(32, (3, 3), activation='relu', input_shape=(100, 100, 3)), MaxPooling2D(pool_size=(2, 2)), Conv2D(64, (3, 3), activation='relu'), MaxPooling2D(pool_size=(2, 2)), Conv2D(128, (3, 3), activation='relu'), MaxPooling2D(pool_size=(2, 2)), Flatten(), Dense(512, activation='relu'), Dropout(0.5), Dense(131, activation='softmax') # 131 classes in the dataset ]) # Compile the model model.compile(optimizer=Adam(), loss='categorical_crossentropy', metrics=['accuracy']) . # Determine steps per epoch and validation steps steps_per_epoch = train_generator.samples // train_generator.batch_size validation_steps = test_generator.samples // test_generator.batch_size . # Evaluate the model loss, accuracy = model.evaluate(test_generator) print(f'Test accuracy: {accuracy * 100:.2f}%') . Found 67692 images belonging to 131 classes. Found 22688 images belonging to 131 classes. C: Users adity AppData Local Programs Python Python312 Lib site-packages keras src layers convolutional base_conv.py:107: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead. super().__init__(activity_regularizer=activity_regularizer, **kwargs) Epoch 1/15 C: Users adity AppData Local Programs Python Python312 Lib site-packages keras src trainers data_adapters py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored. self._warn_if_super_not_called() 2115/2115 ━━━━━━━━━━━━━━━━━━━━ 720s 338ms/step - accuracy: 0.4970 - loss: 1.9714 - val_accuracy: 0.9128 - val_loss: 0.3601 Epoch 2/15  1/2115 ━━━━━━━━━━━━━━━━━━━━ 6:14 177ms/step - accuracy: 0.8750 - loss: 0.2425 C: Users adity AppData Local Programs Python Python312 Lib contextlib.py:158: UserWarning: Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches. You may need to use the `.repeat()` function when building your dataset. self.gen.throw(value) An error occurred: 'NoneType' object has no attribute 'items' 709/709 ━━━━━━━━━━━━━━━━━━━━ 46s 65ms/step - accuracy: 0.9185 - loss: 0.3224 Test accuracy: 91.70% .",
             "url": "http://localhost:4100/adi_student/posts/fruits",
             "relUrl": "/posts/fruits",
             "date": " • Sep 10, 2024"
@@ -174,7 +174,7 @@
 
       ,"page4": {
           "title": "",
-          "content": ". . Click here to view my journey setting up GitHub Pages: . My Journey . . Jupyter Notebooks . Notebooks Fruits Model Emoji Fun! . Rooooooooooter1!!!! . Enter first number: . . Enter second number: . . Add Subtract Divide Multiply . .",
+          "content": ". . Click here to view my journey setting up GitHub Pages: . My Journey . . Jupyter Notebooks . Notebooks Fruits Model Emoji Fun! . Rooooooooooter1!!!! . Enter first number: . . Enter second number: . . Add Subtract Divide Multiply . . The links are not switched. . Click me to switch links! Link #1 Link #2 .",
           "url": "http://localhost:4100/adi_student/",
           "relUrl": "/",
           "date": ""