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AI-generated code refactor #512
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Additional Warning and SolutionWhile running the code, I also encountered the following warning:
Here is how to fix it:
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Handling Time-Series Data and Tide Level Retrieval ErrorsAfter solve the previous warning and error, i encountered several errors related to handling time-series data and retrieving tide levels. The key errors and their solutions are detailed below. Errors and Solutions1. Empty Time Series Dates (
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Handling Missing
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Improvement: Check and Save Preprocessed Image FilesIn this little comment, I want to add a feature that checks if the preprocessed image files already exist in the specified directory before saving new ones. This ensures that we do not perform redundant operations and only save images if they are not already present. Problem DescriptionWhen processing satellite images, it is essential to avoid redundant operations such as re-saving images that have already been preprocessed. This can save time and computational resources. SolutionTo handle this situation, we can use a function to check if the preprocessed image files already exist in the specified directory. If the files do not exist, the script will save the images; otherwise, it will skip this step. Improved Codeimport os
# Function to check if jpg files already exist
def check_files_exist(path, file_extension=".jpg"):
if not os.path.exists(path):
return False
return any(file.endswith(file_extension) for file in os.listdir(path))
# Define the path to preprocessed jpg files in the current directory
preprocessed_path = f"./data/{sitename}/jpg_files/preprocessed"
# Check if directory exists and if files exist
if not os.path.exists(preprocessed_path):
os.makedirs(preprocessed_path)
print(f"Directory created: {preprocessed_path}")
if not check_files_exist(preprocessed_path):
# Only save images if they don't already exist
SDS_preprocess.save_jpg(metadata, settings, use_matplotlib=True)
print("Satellite images saved as .jpg in", preprocessed_path)
else:
print("Preprocessed jpg files already exist in", preprocessed_path) Explanation
This improvement ensures that the script efficiently handles preprocessed image files, avoiding unnecessary reprocessing and saving of files. |
Purpose : Authentication Script for Google Earth EngineThis script is designed to test the connection to Google Earth Engine (GEE) before running example Python scripts. It ensures that the authentication to GEE is successful, allowing further operations with GEE to proceed smoothly. Before executing any Earth Engine scripts, it is crucial to verify that the authentication to Google Cloud is working correctly. This script handles the authentication and initialization process, providing feedback on whether the authentication was successful or not. Script:
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…imelapse animation
Hi @thekester , sorry I didn't have time to review all the changes in your PR. The authentication part is a good improvement, could you please submit only that to a PR? and Integrate it into SDS_downmoad.py? I think it's the only module that requires GEE. |
Hi @kvos Thank you for your feedback! I have updated the PR to include only the authentication function integrated into SDS_download.py, as suggested. In the retrieve_images function within SDS_download.py, I replaced the ee.Initialize() call with authenticate_and_initialize() to ensure complete integration of the authentication process. so i include a new commit on my PR to do that. |
great thanks for that |
IMAGEIO FFMPEG_WRITER WARNING: Resolution Adjustments and Data Alignment for MP4 Timelapse Animation
Hello, after attempting to execute the example.py file, I encountered warnings related to the MP4 timelapse animation. Here is how I resolved the warnings.
Warning Details
Solution
To solve the warning, import the required libraries and use the provided functions to resize the images and create the animation:
but a warning still remains [rawvideo @ 0x67e8680] Stream #0: not enough frames to estimate rate; consider increasing probesize
The text was updated successfully, but these errors were encountered: