{"cells":[{"metadata":{},"cell_type":"markdown","source":"Who hasn't had the opportunity to watch the [fake Obama video?](https://www.youtube.com/watch?v=AmUC4m6w1wo)\n<p>Can you imagine what a video of an influential personality can do in the history of a country? Or even the world?</p>\n"},{"metadata":{},"cell_type":"markdown","source":"<div style=\"text-align: center\"> Left: Real | Right: Fake</div>\n                                                     \n![](https://thumbs.gfycat.com/FantasticFoolishIslandwhistler-size_restricted.gif)\nSource: [BBC News](https://www.bbc.co.uk/news)"},{"metadata":{},"cell_type":"markdown","source":"<p>Deepfake techniques, which present realistic AI-generated videos of people doing and saying fictional things, have the potential to have a significant impact on how people determine the legitimacy of information presented online. These content generation and modification technologies may affect the quality of public discourse and the safeguarding of human rights—especially given that deepfakes may be used maliciously as a source of misinformation, manipulation, harassment, and persuasion.</p>\nSource: [Kaggle.com](https://www.kaggle.com/c/deepfake-detection-challenge)"},{"metadata":{},"cell_type":"markdown","source":"[This post](https://www.kaggle.com/c/deepfake-detection-challenge/discussion/121173#latest-692793) from [@Bojan](https://www.kaggle.com/tunguz) and [this post](https://www.kaggle.com/c/deepfake-detection-challenge/discussion/121183#latest-692784) from [@Bibek](https://www.kaggle.com/bibek777), will be very helpful to the development of this project."},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"_kg_hide-output":true},"cell_type":"code","source":"import numpy as np \nimport pandas as pd \n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"submission = pd.read_csv(\"/kaggle/input/deepfake-detection-challenge/sample_submission.csv\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Submissions are scored on log loss.\nThe answer may be 1 if the video is FAKE, 0 if REAL.\n<p>For each filename in the test set, we must predict a probability for the label variable. The answer probability can range from 0 to 1.</p>\n<p>Here we are arbitrarily setting the result to 0.5, to get an idea of the metric in the LB.</p>"},{"metadata":{"trusted":true},"cell_type":"code","source":"submission['label'] = 0.5\nsubmission.to_csv('submission.csv', index=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission.count()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}