Kvasir-SEG_EffiSegNet-B5/notebook.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyPzd89x18QJ/j8jFo0PPjOD"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UDXwFV5HtdOp","executionInfo":{"status":"ok","timestamp":1754556509656,"user_tz":-345,"elapsed":2034,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"54397ea2-7fd3-4480-faa2-3bd831a3d6f5"},"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'effisegnet'...\n","remote: Enumerating objects: 2050, done.\u001b[K\n","remote: Counting objects: 100% (2050/2050), done.\u001b[K\n","remote: Compressing objects: 100% (1834/1834), done.\u001b[K\n","remote: Total 2050 (delta 221), reused 2032 (delta 211), pack-reused 0 (from 0)\u001b[K\n","Receiving objects: 100% (2050/2050), 18.02 MiB | 19.14 MiB/s, done.\n","Resolving deltas: 100% (221/221), done.\n","/content/effisegnet\n"]}],"source":["!git clone https://github.com/ivezakis/effisegnet.git\n","%cd effisegnet"]},{"cell_type":"code","source":["!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n","!chmod +x Miniconda3-latest-Linux-x86_64.sh\n","!bash ./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local\n","\n","import sys\n","sys.path.append('/usr/local/lib/python3.9/site-packages')\n","\n","!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main\n","!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_D2K2Cfht83L","executionInfo":{"status":"ok","timestamp":1754556559805,"user_tz":-345,"elapsed":29184,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"4641fc05-21b7-4855-b35e-4de7799eb650"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["--2025-08-07 08:48:50--  https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n","Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.32.241, 104.16.191.158, 2606:4700::6810:bf9e, ...\n","Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.32.241|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 160039710 (153M) [application/octet-stream]\n","Saving to: ‘Miniconda3-latest-Linux-x86_64.sh’\n","\n","Miniconda3-latest-L 100%[===================>] 152.62M   195MB/s    in 0.8s    \n","\n","2025-08-07 08:48:51 (195 MB/s) - ‘Miniconda3-latest-Linux-x86_64.sh’ saved [160039710/160039710]\n","\n","PREFIX=/usr/local\n","Unpacking payload ...\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","\n","Installing base environment...\n","\n","Preparing transaction: ...working... done\n","Executing transaction: ...working... done\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","installation finished.\n","WARNING:\n","    You currently have a PYTHONPATH environment variable set. This may cause\n","    unexpected behavior when running the Python interpreter in Miniconda3.\n","    For best results, please verify that your PYTHONPATH only points to\n","    directories of packages that are compatible with the Python interpreter\n","    in Miniconda3: /usr/local\n","accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/main\u001b[0m\n","accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/r\u001b[0m\n"]}]},{"cell_type":"code","source":["!conda env create -f environment.yml"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"VePtIfsyuBPJ","executionInfo":{"status":"ok","timestamp":1754557130096,"user_tz":-345,"elapsed":523220,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"dc0a6b8e-64bf-4715-bf5b-b6111ea860a3"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;32m2\u001b[0m\u001b[1;32m channel Terms of Service accepted\u001b[0m\n","Channels:\n"," - pytorch\n"," - nvidia\n"," - conda-forge\n"," - defaults\n","Platform: linux-64\n","Collecting package metadata (repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n","Solving environment: \\ \b\b| \b\b/ \b\b- \b\bdone\n","\n","\n","==> WARNING: A newer version of conda exists. <==\n","    current version: 25.5.1\n","    latest version: 25.7.0\n","\n","Please update conda by running\n","\n","    $ conda update -n base -c defaults conda\n","\n","\n","\n","Downloading and Extracting Packages:\n","pytorch-2.1.2        | 1.46 GB   | :   0% 0/1 [00:00<?, ?it/s]\n","libcublas-11.11.3.6  | 364.0 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n","\n","libcusparse-11.7.5.8 | 176.3 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","mkl-2023.1.0         | 171.5 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","libnpp-11.8.0.86     | 147.8 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","libcufft-10.9.0.58   | 142.8 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","libcusolver-11.4.1.4 | 96.5 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","torchtriton-2.1.0    | 91.0 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","libcurand-10.3.4.101 | 51.8 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","python-3.11.5        | 32.7 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","cuda-cupti-11.8.87   | 25.3 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","scipy-1.11.4         | 22.0 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","cuda-nvrtc-11.8.89   | 19.1 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","intel-openmp-2023.1. | 17.2 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","sympy-1.12           | 14.4 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","ffmpeg-4.3           | 9.9 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","torchvision-0.16.2   | 8.3 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","numpy-base-1.26.2    | 8.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","botocore-1.34.1      | 6.4 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n"," ... 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\b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n","Executing transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n","Installing pip dependencies: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ Ran pip subprocess with arguments:\n","['/usr/local/envs/effisegnet/bin/python', '-m', 'pip', 'install', '-U', '-r', '/content/effisegnet/condaenv.43k8mzat.requirements.txt', '--exists-action=b']\n","Pip subprocess output:\n","Collecting albumentations==1.3.1 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 1))\n","  Downloading albumentations-1.3.1-py3-none-any.whl.metadata (34 kB)\n","Collecting antlr4-python3-runtime==4.9.3 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 2))\n","  Downloading antlr4-python3-runtime-4.9.3.tar.gz (117 kB)\n","     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 117.0/117.0 kB 6.0 MB/s eta 0:00:00\n","  Preparing metadata (setup.py): started\n","  Preparing metadata (setup.py): finished with status 'done'\n","Collecting contourpy==1.2.0 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 3))\n","  Downloading contourpy-1.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.8 kB)\n","Collecting cycler==0.12.1 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 4))\n","  Downloading cycler-0.12.1-py3-none-any.whl.metadata (3.8 kB)\n","Collecting fonttools==4.47.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 5))\n","  Downloading fonttools-4.47.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (157 kB)\n","     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 157.6/157.6 kB 13.9 MB/s eta 0:00:00\n","Collecting hydra-core==1.3.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 6))\n","  Downloading hydra_core-1.3.2-py3-none-any.whl.metadata (5.5 kB)\n","Collecting imageio==2.33.1 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 7))\n","  Downloading imageio-2.33.1-py3-none-any.whl.metadata (4.9 kB)\n","Collecting joblib==1.3.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 8))\n","  Downloading joblib-1.3.2-py3-none-any.whl.metadata (5.4 kB)\n","Collecting kiwisolver==1.4.5 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 9))\n","  Downloading kiwisolver-1.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.4 kB)\n","Collecting lazy-loader==0.3 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 10))\n","  Downloading lazy_loader-0.3-py3-none-any.whl.metadata (4.3 kB)\n","Collecting matplotlib==3.8.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 11))\n","  Downloading matplotlib-3.8.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.8 kB)\n","Collecting omegaconf==2.3.0 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 12))\n","  Downloading omegaconf-2.3.0-py3-none-any.whl.metadata (3.9 kB)\n","Collecting opencv-python-headless==4.8.1.78 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 13))\n","  Downloading opencv_python_headless-4.8.1.78-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB)\n","Collecting pandas==2.2.0 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 14))\n","  Downloading pandas-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB)\n","Collecting pyparsing==3.1.1 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 15))\n","  Downloading pyparsing-3.1.1-py3-none-any.whl.metadata (5.1 kB)\n","Collecting qudida==0.0.4 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 16))\n","  Downloading qudida-0.0.4-py3-none-any.whl.metadata (1.5 kB)\n","Collecting scikit-image==0.22.0 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 17))\n","  Downloading scikit_image-0.22.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (13 kB)\n","Collecting scikit-learn==1.3.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 18))\n","  Downloading scikit_learn-1.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB)\n","Collecting seaborn==0.13.2 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 19))\n","  Downloading seaborn-0.13.2-py3-none-any.whl.metadata (5.4 kB)\n","Collecting threadpoolctl==3.2.0 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 20))\n","  Downloading threadpoolctl-3.2.0-py3-none-any.whl.metadata (10.0 kB)\n","Collecting tifffile==2023.12.9 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 21))\n","  Downloading tifffile-2023.12.9-py3-none-any.whl.metadata (31 kB)\n","Collecting tzdata==2023.4 (from -r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 22))\n","  Downloading tzdata-2023.4-py2.py3-none-any.whl.metadata (1.4 kB)\n","Requirement already satisfied: numpy>=1.11.1 in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from albumentations==1.3.1->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 1)) (1.26.2)\n","Requirement already satisfied: scipy>=1.1.0 in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from albumentations==1.3.1->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 1)) (1.11.4)\n","Requirement already satisfied: PyYAML in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from albumentations==1.3.1->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 1)) (6.0.1)\n","Requirement already satisfied: packaging in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from hydra-core==1.3.2->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 6)) (23.2)\n","Requirement already satisfied: pillow>=8.3.2 in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from imageio==2.33.1->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 7)) (10.0.1)\n","Requirement already satisfied: python-dateutil>=2.7 in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from matplotlib==3.8.2->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 11)) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/envs/effisegnet/lib/python3.11/site-packages (from pandas==2.2.0->-r /content/effisegnet/condaenv.43k8mzat.requirements.txt (line 14)) (2023.3.post1)\n","Requirement already satisfied: typing-extensions in 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activate this environment, use\n","#\n","#     $ conda activate effisegnet\n","#\n","# To deactivate an active environment, use\n","#\n","#     $ conda deactivate\n","\n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate effisegnet && python train.py"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CXOLVnXpwTny","executionInfo":{"status":"ok","timestamp":1754557694965,"user_tz":-345,"elapsed":516956,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"3ccefa82-407e-45a4-d599-343a48339dc7"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Seed set to 42\n","Downloading: \"https://github.com/lukemelas/EfficientNet-PyTorch/releases/download/1.0/efficientnet-b0-355c32eb.pth\" to /root/.cache/torch/hub/checkpoints/efficientnet-b0-355c32eb.pth\n","100% 20.4M/20.4M [00:00<00:00, 71.0MB/s]\n","GPU available: True (cuda), used: True\n","TPU available: False, using: 0 TPU cores\n","IPU available: False, using: 0 IPUs\n","HPU available: False, using: 0 HPUs\n","Missing logger folder: logs/efficientnet-b0_32\n","LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n","\n","  | Name      | Type         | Params\n","-------------------------------------------\n","0 | model     | EffiSegNetBN | 4.2 M \n","1 | criterion | DiceCELoss   | 0     \n","-------------------------------------------\n","4.2 M     Trainable params\n","0         Non-trainable params\n","4.2 M     Total params\n","16.627    Total estimated model params size (MB)\n","Sanity Checking DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/envs/effisegnet/lib/python3.11/site-packages/monai/losses/dice.py:161: UserWarning: single channel prediction, `include_background=False` ignored.\n","  warnings.warn(\"single channel prediction, `include_background=False` ignored.\")\n","Epoch 0: 100% 100/100 [00:43<00:00,  2.28it/s, v_num=0]\n","Validation: |          | 0/? 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[00:00<?, ?it/s]\u001b[A\n","Validation:   0% 0/13 [00:00<?, ?it/s]       \u001b[A\n","Validation DataLoader 0:   0% 0/13 [00:00<?, ?it/s]\u001b[A\n","Validation DataLoader 0: 100% 13/13 [00:00<00:00, 19.47it/s]\u001b[A\n","Epoch 10:  80% 80/100 [00:35<00:08,  2.25it/s, v_num=0]/usr/local/envs/effisegnet/lib/python3.11/site-packages/lightning/pytorch/trainer/call.py:54: Detected KeyboardInterrupt, attempting graceful shutdown...\n","LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n","Testing DataLoader 0: 100% 13/13 [00:00<00:00, 19.64it/s]\n","┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n","┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n","┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n","│\u001b[36m \u001b[0m\u001b[36m        test_dice        \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8286120891571045    \u001b[0m\u001b[35m \u001b[0m│\n","│\u001b[36m \u001b[0m\u001b[36m         test_f1         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8759540915489197    \u001b[0m\u001b[35m \u001b[0m│\n","│\u001b[36m \u001b[0m\u001b[36m        test_iou         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.7286696434020996    \u001b[0m\u001b[35m \u001b[0m│\n","│\u001b[36m \u001b[0m\u001b[36m        test_loss        \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.6491853594779968    \u001b[0m\u001b[35m \u001b[0m│\n","│\u001b[36m \u001b[0m\u001b[36m     test_precision      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8149681687355042    \u001b[0m\u001b[35m \u001b[0m│\n","│\u001b[36m \u001b[0m\u001b[36m       test_recall       \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.9468057751655579    \u001b[0m\u001b[35m \u001b[0m│\n","└───────────────────────────┴───────────────────────────┘\n","Epoch 10:  80% 80/100 [00:38<00:09,  2.09it/s, v_num=0]\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"gdrbUJiqwd9n"},"execution_count":null,"outputs":[]}]}