![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F1182060%2F473dfd70dd2d9e278dd5076310583766%2FRainforest%20diagram.jpg?generation=1611227361853675&alt=media\")
Hi everyone, I find that this competition could be a good opportunity to finally try to apply machine learning to audio data, there is already a lot of available public notebooks with very good scores, but even being familiar with deep learning and Tensorflow I was having a hard time to understand everything that was going on (sometimes Tensorflow does that). So I wrote a notebook that has the basics for audio classification with Tensorflow, putting everything together in a more organized way, and added documentation to some of the methods, you can find it here Rainforest - Audio classification Tensorflow starter
\nI also made a workflow diagram to make things visual.
\n1. Load TFRecords\n2. Decode audio waveform\n3. Crop audio waveform\n4. Convert the waveform into spectrogram\n4. Resize spectrogram\n5. Turn grayscale spectrogram into RGB image\n6. Feed to the model\n
Hi everyone, I find that this competition could be a good opportunity to finally try to apply machine learning to audio data, there is already a lot of available public notebooks with very good scores, but even being familiar with deep learning and Tensorflow I was having a hard time to understand everything that was going on (sometimes Tensorflow does that). So I wrote a notebook that has the basics for audio classification with Tensorflow, putting everything together in a more organized way, and added documentation to some of the methods, you can find it here Rainforest - Audio classification Tensorflow starter
\nI also made a workflow diagram to make things visual.
\n1. Load TFRecords\n2. Decode audio waveform\n3. Crop audio waveform\n4. Convert the waveform into spectrogram\n4. Resize spectrogram\n5. Turn grayscale spectrogram into RGB image\n6. Feed to the model\n
Good work, Congrats! :)
", "rawMarkdown": "Good work, Congrats! :) ", "votes": 1 }, { "id": 1168308, "postDate": "2021-01-24T21:18:43.257Z", "content": "Thank you for sharing the great Discussion and Notebook!
\nTheses are helpful for me!
That is a very nice chart made specifically for this competition :)
", "rawMarkdown": "That is a very nice chart made specifically for this competition :)", "votes": 1, "replies": [ { "id": 1163696, "postDate": "2021-01-21T21:29:26.750Z", "content": "Yeah @barnwellguy , figuring everything at a higher level just looking at Tensorflow code can be hard 😄
", "rawMarkdown": "Yeah @barnwellguy , figuring everything at a higher level just looking at Tensorflow code can be hard 😄", "votes": 1 }, { "id": 1163719, "postDate": "2021-01-21T22:01:30.583Z", "content": "Yeah @dimitreoliveira I strongly agree! 🔥
\nNow that we have good image captioning tools to give a short introduction sentence for a picture.
\nWhy don't we have a code captioning tool to give big ideas of each chunk of code?
\n\"These ten lines are loading data\",
\n\"These twenty lines are training a NN\",
\n\"These thirty lines don't even possibly run.\"
That would save tremendous amount of anxiety learning an unfamiliar piece of code.
", "rawMarkdown": "Yeah @dimitreoliveira I strongly agree! 🔥\n\nNow that we have good image captioning tools to give a short introduction sentence for a picture.\n\nWhy don't we have a code captioning tool to give big ideas of each chunk of code? \n\"These ten lines are loading data\", \n\"These twenty lines are training a NN\", \n\"These thirty lines don't even possibly run.\"\n\nThat would save tremendous amount of anxiety learning an unfamiliar piece of code.", "votes": 1 }, { "id": 1163796, "postDate": "2021-01-22T00:05:48.853Z", "content": "I agree @barnwellguy , I usually lose myself going through PyTorch code.
\nWhen I share public code, I try to use functions whenever I can, I also give them intuitive names and if needed a text docummentation, usually help even myself when I go through the code sometime later.
", "rawMarkdown": "I agree @barnwellguy , I usually lose myself going through PyTorch code.\n\nWhen I share public code, I try to use functions whenever I can, I also give them intuitive names and if needed a text docummentation, usually help even myself when I go through the code sometime later.", "votes": 2 }, { "id": 1168380, "postDate": "2021-01-24T22:54:18.727Z", "content": "Hi @barnwellguy and @dimitreoliveira
\nThere is a nice github repo which shows the codes with the explanations by side. It's not a tool but very useful. https://github.com/lab-ml/nn
", "rawMarkdown": "Hi @barnwellguy and @dimitreoliveira \n\nThere is a nice github repo which shows the codes with the explanations by side. It's not a tool but very useful. [https://github.com/lab-ml/nn](https://github.com/lab-ml/nn)", "votes": 1 }, { "id": 1168466, "postDate": "2021-01-25T00:44:01.490Z", "content": "Thanks @snnclsr , that is a very useful repo, I can only imagine how hard was to build that.
", "rawMarkdown": "Thanks @snnclsr , that is a very useful repo, I can only imagine how hard was to build that." } ] }, { "id": 1163237, "postDate": "2021-01-21T15:50:56.253Z", "content": "Thanks for sharing, I was looking out for a notebook for beginners to get started in this competition.
", "rawMarkdown": "Thanks for sharing, I was looking out for a notebook for beginners to get started in this competition.", "votes": 1, "replies": [ { "id": 1163697, "postDate": "2021-01-21T21:30:15.467Z", "content": "Nice @sajidhussain3 , note that this is just a weak baseline, the idea is to get you familiar with the basics of audio classification, and how to use Tensorflow for this task.
", "rawMarkdown": "Nice @sajidhussain3 , note that this is just a weak baseline, the idea is to get you familiar with the basics of audio classification, and how to use Tensorflow for this task.", "votes": 1 } ] }, { "id": 2581845, "postDate": "2024-01-01T06:30:11.327Z", "content": "valuable information
", "rawMarkdown": "valuable information" }, { "id": 1163238, "postDate": "2021-01-21T15:50:56.253Z", "rawMarkdown": "", "isDeleted": true }, { "id": 1162878, "postDate": "2021-01-21T11:43:45.377Z", "rawMarkdown": "", "votes": -1, "isDeleted": true }, { "id": 1177173, "postDate": "2021-01-30T05:44:53.850Z", "content": "Thanks for sharing. :)
", "rawMarkdown": "Thanks for sharing. :)", "votes": 1 }, { "id": 1172683, "postDate": "2021-01-27T13:53:13.967Z", "content": "Thanks for sharing :D
", "rawMarkdown": "Thanks for sharing :D", "votes": 1 }, { "id": 1171333, "postDate": "2021-01-26T19:22:27.633Z", "content": "Thanks for sharing!
", "rawMarkdown": "Thanks for sharing!", "votes": 1 }, { "id": 1162837, "postDate": "2021-01-21T11:23:03.647Z", "content": "Great work, Thank you!!🙌
", "rawMarkdown": "Great work, Thank you!!🙌", "votes": 1 }, { "id": 2984092, "postDate": "2024-09-09T11:22:26.243Z", "content": "thanks to you. I really appreciate
", "rawMarkdown": "thanks to you. I really appreciate" } ], "comments": [ { "id": 1199859, "author_name": "Miguel Angel Velazquez Romero", "author_url": "", "post_date": "2021-02-14T06:43:30.950000", "content": "Good work, Congrats! :)
", "votes": 1, "replies": [] }, { "id": 1168308, "author_name": "ANZ", "author_url": "", "post_date": "2021-01-24T21:18:43.257000", "content": "Thank you for sharing the great Discussion and Notebook!
\nTheses are helpful for me!
That is a very nice chart made specifically for this competition :)
", "votes": 1, "replies": [ { "id": 1163696, "author_name": "DimitreOliveira", "author_url": "", "post_date": "2021-01-21T21:29:26.750000", "content": "Yeah @barnwellguy , figuring everything at a higher level just looking at Tensorflow code can be hard 😄
", "votes": 1, "replies": [] }, { "id": 1163719, "author_name": "Buffalo Spdwy", "author_url": "", "post_date": "2021-01-21T22:01:30.583000", "content": "Yeah @dimitreoliveira I strongly agree! 🔥
\nNow that we have good image captioning tools to give a short introduction sentence for a picture.
\nWhy don't we have a code captioning tool to give big ideas of each chunk of code?
\n\"These ten lines are loading data\",
\n\"These twenty lines are training a NN\",
\n\"These thirty lines don't even possibly run.\"
That would save tremendous amount of anxiety learning an unfamiliar piece of code.
", "votes": 1, "replies": [] }, { "id": 1163796, "author_name": "DimitreOliveira", "author_url": "", "post_date": "2021-01-22T00:05:48.853000", "content": "I agree @barnwellguy , I usually lose myself going through PyTorch code.
\nWhen I share public code, I try to use functions whenever I can, I also give them intuitive names and if needed a text docummentation, usually help even myself when I go through the code sometime later.
", "votes": 2, "replies": [] }, { "id": 1168380, "author_name": "Sinan Calisir", "author_url": "", "post_date": "2021-01-24T22:54:18.727000", "content": "Hi @barnwellguy and @dimitreoliveira
\nThere is a nice github repo which shows the codes with the explanations by side. It's not a tool but very useful. https://github.com/lab-ml/nn
", "votes": 1, "replies": [] }, { "id": 1168466, "author_name": "DimitreOliveira", "author_url": "", "post_date": "2021-01-25T00:44:01.490000", "content": "Thanks @snnclsr , that is a very useful repo, I can only imagine how hard was to build that.
", "votes": 0, "replies": [] } ] }, { "id": 1163237, "author_name": "Sajid Hussain", "author_url": "", "post_date": "2021-01-21T15:50:56.253000", "content": "Thanks for sharing, I was looking out for a notebook for beginners to get started in this competition.
", "votes": 1, "replies": [ { "id": 1163697, "author_name": "DimitreOliveira", "author_url": "", "post_date": "2021-01-21T21:30:15.467000", "content": "Nice @sajidhussain3 , note that this is just a weak baseline, the idea is to get you familiar with the basics of audio classification, and how to use Tensorflow for this task.
", "votes": 1, "replies": [] } ] }, { "id": 2581845, "author_name": "Sumit Kumar Singh", "author_url": "", "post_date": "2024-01-01T06:30:11.327000", "content": "valuable information
", "votes": 0, "replies": [] }, { "id": 1163238, "author_name": "", "author_url": "", "post_date": "2021-01-21T15:50:56.253000", "content": "", "votes": 0, "replies": [] }, { "id": 1162878, "author_name": "", "author_url": "", "post_date": "2021-01-21T11:43:45.377000", "content": "", "votes": -1, "replies": [] }, { "id": 1177173, "author_name": "Aman Goyal", "author_url": "", "post_date": "2021-01-30T05:44:53.850000", "content": "Thanks for sharing. :)
", "votes": 1, "replies": [] }, { "id": 1172683, "author_name": "Michael Jackson", "author_url": "", "post_date": "2021-01-27T13:53:13.967000", "content": "Thanks for sharing :D
", "votes": 1, "replies": [] }, { "id": 1171333, "author_name": "rtldr5", "author_url": "", "post_date": "2021-01-26T19:22:27.633000", "content": "Thanks for sharing!
", "votes": 1, "replies": [] }, { "id": 1162837, "author_name": "Ankush kuwar", "author_url": "", "post_date": "2021-01-21T11:23:03.647000", "content": "Great work, Thank you!!🙌
", "votes": 1, "replies": [] }, { "id": 2984092, "author_name": "Arielle Sezine", "author_url": "", "post_date": "2024-09-09T11:22:26.243000", "content": "thanks to you. I really appreciate
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1162825": "Hi everyone, I find that this competition could be a good opportunity to finally try to apply machine learning to audio data, there is already a lot of available public notebooks with very good scores, but even being familiar with deep learning and Tensorflow I was having a hard time to understand everything that was going on (sometimes Tensorflow does that). So I wrote a notebook that has the basics for audio classification with Tensorflow, putting everything together in a more organized way, and added documentation to some of the methods, you can find it here [Rainforest - Audio classification Tensorflow starter](https://www.kaggle.com/dimitreoliveira/rainforest-audio-classification-tensorflow-starter/notebook)\n\nI also made a workflow diagram to make things visual.\n```\n1. Load TFRecords\n2. Decode audio waveform\n3. Crop audio waveform\n4. Convert the waveform into spectrogram\n4. Resize spectrogram\n5. Turn grayscale spectrogram into RGB image\n6. Feed to the model\n```\n\n\n---\n\n#### A few ideas for improvements\n- Add data augmentation\n- Try different encoders (people seems to get good results with ResNet variants)\n- Different losses\n- Convert spectrogram to Mel-spectrogram\n- Add more layers at the top of the encoder\n- K-Fold\n- [Better crop](https://www.kaggle.com/c/rfcx-species-audio-detection/discussion/200922)\n- Some of the things discussed [here](https://www.kaggle.com/c/rfcx-species-audio-detection/discussion/208830)", "1199859": "Good work, Congrats! :) ", "1168308": "Thank you for sharing the great Discussion and Notebook!\nTheses are helpful for me!", "1163681": "That is a very nice chart made specifically for this competition :)", "1163237": "Thanks for sharing, I was looking out for a notebook for beginners to get started in this competition.", "2581845": "valuable information", "1163238": "", "1162878": "", "1177173": "Thanks for sharing. :)", "1172683": "Thanks for sharing :D", "1171333": "Thanks for sharing!", "1162837": "Great work, Thank you!!🙌", "2984092": "thanks to you. I really appreciate" } }