From f4ec2f456d6124a356c737796c2d37399e211498 Mon Sep 17 00:00:00 2001 From: Reddy Yaswanth <152393508+Reddyyaswanthts@users.noreply.github.com> Date: Mon, 20 May 2024 16:41:26 +0530 Subject: [PATCH 1/5] Task1 --- REDDY YASWANTH/Task1 | 36 ++++++++++++++++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 REDDY YASWANTH/Task1 diff --git a/REDDY YASWANTH/Task1 b/REDDY YASWANTH/Task1 new file mode 100644 index 0000000..8f8b98b --- /dev/null +++ b/REDDY YASWANTH/Task1 @@ -0,0 +1,36 @@ +from PIL import Image +import os + +def convert_image(input_path, output_path, output_format): + try: + # Open the image + with Image.open(input_path) as img: + # Convert and save the image to the desired format + img.save(output_path, format=output_format) + print(f"Image converted successfully to {output_format} format.") + except Exception as e: + print(f"An error occurred: {e}") + +def main(): + input_path = input("Enter the path to the input image: ") + output_format = input("Enter the desired output format (e.g., JPEG, PNG, BMP, GIF): ").upper() + + # Validate output format + if output_format not in ['JPEG', 'PNG', 'BMP', 'GIF']: + print("Invalid output format. Please choose from JPEG, PNG, BMP, or GIF.") + return + + # Extract the file name and extension + file_name, file_extension = os.path.splitext(input_path) + + # If the input file already has an extension, remove it + file_name_without_ext = file_name.split('.')[0] + + # Set the output path + output_path = f"{file_name_without_ext}_converted.{output_format.lower()}" + + # Convert the image + convert_image(input_path, output_path, output_format) + +if __name__ == "__main__": +    main() From 82f198221200d57d17ba4975cb706081e70b2e87 Mon Sep 17 00:00:00 2001 From: Reddy Yaswanth <152393508+Reddyyaswanthts@users.noreply.github.com> Date: Mon, 20 May 2024 16:42:38 +0530 Subject: [PATCH 2/5] Task2 --- REDDY YASWANTH/Task2 | 43 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 43 insertions(+) create mode 100644 REDDY YASWANTH/Task2 diff --git a/REDDY YASWANTH/Task2 b/REDDY YASWANTH/Task2 new file mode 100644 index 0000000..2fee7c7 --- /dev/null +++ b/REDDY YASWANTH/Task2 @@ -0,0 +1,43 @@ +import seaborn as sns +import pandas as pd +import matplotlib.pyplot as plt + +# Load the Iris dataset from Seaborn +iris = sns.load_dataset("iris") +numeric_iris = iris.drop(columns='species') + +# Display the first few rows of the dataset +print("First few rows of the dataset:") +print(iris.head()) + +# Summary statistics +print("\nSummary statistics:") +print(iris.describe()) + +# Checking for missing values +print("\nMissing values:") +print(iris.isnull().sum()) + +# Visualizations +# Pairplot +sns.pairplot(iris, hue="species") +plt.title("Pairplot of Iris Dataset") +plt.show() + +# Boxplot +plt.figure(figsize=(10, 6)) +sns.boxplot(data=iris, orient="h") +plt.title("Boxplot of Iris Dataset") +plt.show() + +# Histograms +plt.figure(figsize=(10, 6)) +iris.hist() +plt.suptitle("Histograms of Iris Dataset") +plt.show() + +# Correlation heatmap +plt.figure(figsize=(8, 6)) +sns.heatmap(numeric_iris.corr(), annot=True, cmap="coolwarm") +plt.title("Correlation Heatmap of Iris Dataset") +plt.show() From 8ce8f14d74740c723cd4c230eacff2fe76af377a Mon Sep 17 00:00:00 2001 From: Reddy Yaswanth <152393508+Reddyyaswanthts@users.noreply.github.com> Date: Mon, 20 May 2024 16:44:16 +0530 Subject: [PATCH 3/5] Task3 --- REDDY YASWANTH/Task3 | 45 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 REDDY YASWANTH/Task3 diff --git a/REDDY YASWANTH/Task3 b/REDDY YASWANTH/Task3 new file mode 100644 index 0000000..5bb8616 --- /dev/null +++ b/REDDY YASWANTH/Task3 @@ -0,0 +1,45 @@ +import numpy as np +import matplotlib.pyplot as plt +from sklearn.model_selection import train_test_split +from sklearn.linear_model import LinearRegression +from sklearn.metrics import mean_squared_error +import pandas as pd +data_url = "http://lib.stat.cmu.edu/datasets/boston" +raw_df = pd.read_csv(data_url, sep="\s+", skiprows=22, header=None) +data = np.hstack([raw_df.values[::2, :], raw_df.values[1::2, :2]]) +target = raw_df.values[1::2, 2] + +# Load the Boston housing dataset + +X = data +y = target + +# Split the data into training and testing sets +X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) + +# Initialize the linear regression model +model = LinearRegression() + +# Fit the model on the training data +model.fit(X_train, y_train) + +# Predict on the training and testing data +y_train_pred = model.predict(X_train) +y_test_pred = model.predict(X_test) + +# Calculate the scores +train_score = model.score(X_train, y_train) +test_score = model.score(X_test, y_test) + +print("Training score:", train_score) +print("Testing score:", test_score) + +# Plot residuals +plt.scatter(y_train_pred, y_train_pred - y_train, c='blue', marker='o', label='Training data') +plt.scatter(y_test_pred, y_test_pred - y_test, c='lightgreen', marker='s', label='Testing data') +plt.xlabel('Predicted values') +plt.ylabel('Residuals') +plt.legend(loc='upper left') +plt.hlines(y=0, xmin=0, xmax=50, lw=2, color='red') +plt.title('Residual plot') +plt.show() From b0cba76fb752e874d01419ed340dee217a43df39 Mon Sep 17 00:00:00 2001 From: Reddy Yaswanth <152393508+Reddyyaswanthts@users.noreply.github.com> Date: Mon, 20 May 2024 16:46:25 +0530 Subject: [PATCH 4/5] Task4 In place of wp1966881.jpg you can add any other example image. --- REDDY YASWANTH/Task4 | 52 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 REDDY YASWANTH/Task4 diff --git a/REDDY YASWANTH/Task4 b/REDDY YASWANTH/Task4 new file mode 100644 index 0000000..4616456 --- /dev/null +++ b/REDDY YASWANTH/Task4 @@ -0,0 +1,52 @@ +from PIL import Image +import os + +def get_size_format(b, factor=1024, suffix="B"): + """ + Scale bytes to its proper byte format. + e.g: 1253656 => '1.20MB', 1253656678 => '1.17GB' + """ + for unit in ["", "K", "M", "G", "T", "P", "E", "Z"]: + if b < factor: + return f"{b:.2f}{unit}{suffix}" + b /= factor + return f"{b:.2f}Y{suffix}" + +def compress_img(image_name, new_size_ratio=0.9, quality=90, width=None, height=None, to_jpg=True): + # Load the image into memory + img = Image.open(image_name) + + # Print the original image shape + print("[*] Image shape:", img.size) + + # Get the original image size in bytes + image_size = os.path.getsize(image_name) + print("[*] Size before compression:", get_size_format(image_size)) + + if new_size_ratio < 1.0: + # If resizing ratio is below 1.0, multiply width & height with this ratio to reduce image size + img = img.resize((int(img.size[0] * new_size_ratio), int(img.size[1] * new_size_ratio)), Image.ANTIALIAS) + elif width and height: + # If width and height are set, resize with them instead + img = img.resize((width, height), Image.ANTIALIAS) + + # Split the filename and extension + filename, ext = os.path.splitext(image_name) + + # Make a new filename appending "_compressed" to the original file name + if to_jpg: + # Change the extension to JPEG + new_filename = f"{filename}_compressed.jpg" + else: + # Retain the same extension of the original image + new_filename = f"{filename}_compressed{ext}" + + # Save the compressed image + img.save(new_filename, optimize=True, quality=quality) + + # Print the new image shape + print("[+] New Image shape:", img.size) + print(f"[*] Compressed image saved as: {new_filename}") + +# Example usage: +compress_img("wp1966881.jpg", new_size_ratio=0.8, quality=80, width=800, height=600) From 7de2b44565d693613ee9a40366c30a12cb1bdbc1 Mon Sep 17 00:00:00 2001 From: Reddy Yaswanth <152393508+Reddyyaswanthts@users.noreply.github.com> Date: Mon, 20 May 2024 16:49:48 +0530 Subject: [PATCH 5/5] README.md --- REDDY YASWANTH/README.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 REDDY YASWANTH/README.md diff --git a/REDDY YASWANTH/README.md b/REDDY YASWANTH/README.md new file mode 100644 index 0000000..dc62a02 --- /dev/null +++ b/REDDY YASWANTH/README.md @@ -0,0 +1,20 @@ +Advance Level + +Task 1 :Image Converter: + +Where the program that accepts images in multiple formats that may be in JPEG, PNG, BMP, GIF and converts them into a desired format using Python Imaging Library (PIL) that may be any of the formats mentioned. + + +Task 2:Data Analysis with Pandas: + +In the program on loading the "Iris" dataset from Seaborn and analyzing it using Pandas and performed exploratory data analysis, cleaning, aggregation, visualizations, and correlation calculations. +The output of the program will consits of calculations , graph which will be more understanding to users. + + +Task 3:Linear Regression with Scikit-learn: + +Completed a program by applying linear regression to predict house prices from the Boston housing dataset using scikit-learn and compared train and test scores and plot residuals. + +Task 4:Image Compression: + +Developed a Python program for compressing images while maintaining quality by exploring compression techniques like RLE and DCT and allowing users to adjust compression quality, support various image formats, and provide output options. Optionally, include a user interface.