NORLIE JHON MALAGDAO commited on
Commit
2116a66
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1 Parent(s): 5f80dfa

Update app.py

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Files changed (1) hide show
  1. app.py +76 -0
app.py CHANGED
@@ -1,3 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  batch_size = 32
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  img_height = 180
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  img_width = 180
 
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+ import gradio as gr
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+ import matplotlib.pyplot as plt
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+ import numpy as np
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+ import os
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+ import PIL
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+ import tensorflow as tf
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+
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+ from tensorflow import keras
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+ from tensorflow.keras import layers
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+ from tensorflow.keras.models import Sequential
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+
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+
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+ from PIL import Image
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+ import gdown
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+ import zipfile
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+
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+ import pathlib
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+
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+
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+
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+
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+
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+ # Define the Google Drive shareable link
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+ gdrive_url = 'https://drive.google.com/file/d/1HjHYlQyRz5oWt8kehkt1TiOGRRlKFsv8/view?usp=drive_link'
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+
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+ # Extract the file ID from the URL
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+ file_id = gdrive_url.split('/d/')[1].split('/view')[0]
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+ direct_download_url = f'https://drive.google.com/uc?id={file_id}'
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+
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+ # Define the local filename to save the ZIP file
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+ local_zip_file = 'file.zip'
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+
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+ # Download the ZIP file
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+ gdown.download(direct_download_url, local_zip_file, quiet=False)
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+
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+ # Directory to extract files
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+ extracted_path = 'extracted_files'
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+
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+ # Verify if the downloaded file is a ZIP file and extract it
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+ try:
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+ with zipfile.ZipFile(local_zip_file, 'r') as zip_ref:
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+ zip_ref.extractall(extracted_path)
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+ print("Extraction successful!")
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+ except zipfile.BadZipFile:
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+ print("Error: The downloaded file is not a valid ZIP file.")
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+
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+ # Optionally, you can delete the ZIP file after extraction
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+ os.remove(local_zip_file)
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+
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+ # Convert the extracted directory path to a pathlib.Path object
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+ data_dir = pathlib.Path(extracted_path)
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+
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+ # Print the directory structure to debug
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+ for root, dirs, files in os.walk(extracted_path):
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+ level = root.replace(extracted_path, '').count(os.sep)
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+ indent = ' ' * 4 * (level)
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+ print(f"{indent}{os.path.basename(root)}/")
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+ subindent = ' ' * 4 * (level + 1)
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+ for f in files:
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+ print(f"{subindent}{f}")
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+
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+ import pathlib
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+ # Path to the dataset directory
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+ data_dir = pathlib.Path('extracted_files/Pest_Dataset')
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+ data_dir = pathlib.Path(data_dir)
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+
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+
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+ bees = list(data_dir.glob('bees/*'))
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+ print(bees[0])
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+ PIL.Image.open(str(bees[0]))
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+
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+
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+ bees = list(data_dir.glob('bees/*'))
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+ print(bees[0])
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+ PIL.Image.open(str(bees[0]))
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+
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  batch_size = 32
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  img_height = 180
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  img_width = 180