very rough first demo

.gitignore

@@ -0,0 +1,163 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+*venv*
+.env
+# C extensions
+*.so
+env
+env/
+model/
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

app.py

@@ -0,0 +1,56 @@
+import gradio as gr
+import cv2 
+
+import numpy as np
+import gradio as gr
+ 
+from inference import inference_frame
+import os
+
+
+
+
+def analize_video(x):
+    cap = cv2.VideoCapture(x)
+    path = '/tmp/test/'
+    os.makedirs(path, exist_ok=True)
+    videos = len(os.listdir(path))
+    path = f'{path}{videos}'
+    os.makedirs(path, exist_ok=True)
+    outname = f'{path}_processed.mp4'
+    #out = cv2.VideoWriter(outname,cv2.VideoWriter_fourcc(*'h264'), 20.0, (640,480))
+    counter = 0
+    while(cap.isOpened()):
+        ret, frame = cap.read()
+        if ret==True:
+            name = os.path.join(path,f'{counter:05d}.png')
+            frame = inference_frame(frame)
+            # write the flipped frame
+            cv2.imwrite(name, frame)
+            counter +=1 
+        else:
+            break
+    # Release everything if job is finished
+    print(path)
+    os.system(f'''ffmpeg -framerate 20 -pattern_type glob -i '{path}/*.png'  -c:v libx264 -pix_fmt yuv420p {outname}''')
+    return outname
+
+with gr.Blocks(title='Shark Patrol',theme=gr.themes.Soft(),live=True,) as demo:
+    gr.Markdown("Initial DEMO.")
+    with gr.Tab("Shark Detector"):
+        with gr.Row():
+            video_input = gr.Video(source='upload',include_audio=False)
+            #video_input.style(witdh='50%',height='50%')
+            video_output = gr.Video()
+            #video_output.style(witdh='50%',height='50%')
+        
+        video_button = gr.Button("Analyze")
+
+
+    with gr.Accordion("Open for More!"):
+        gr.Markdown("Place holder for detection")
+
+    video_button.click(analize_video, inputs=video_input, outputs=video_output)
+   
+demo.queue()
+demo.launch(share=True,width='40%',auth=(os.environ.get('SHARK_USERNAME'), os.environ.get('SHARK_PASSWORD')))

inference.py

@@ -0,0 +1,113 @@
+# Check Pytorch installation
+import torch, torchvision
+print("torch version:",torch.__version__, "cuda:",torch.cuda.is_available())
+
+# Check MMDetection installation
+import mmdet
+import os
+import mmcv
+import mmengine
+from mmdet.apis import init_detector, inference_detector
+from mmdet.utils import register_all_modules
+from mmdet.registry import VISUALIZERS
+
+from huggingface_hub import hf_hub_download
+from huggingface_hub import snapshot_download
+
+
+classes= ['Beach',
+ 'Sea',
+ 'Wave',
+ 'Rock',
+ 'Breaking wave',
+ 'Reflection of the sea',
+ 'Foam',
+ 'Algae',
+ 'Vegetation',
+ 'Watermark',
+ 'Bird',
+ 'Ship',
+ 'Boat',
+ 'Car',
+ 'Kayak',
+ "Shark's line",
+ 'Dock',
+ 'Dog',
+ 'Unidentifiable shade',
+ 'Bird shadow',
+ 'Boat shadow',
+ 'Kayal shade',
+ 'Surfer shadow',
+ 'Shark shadow',
+ 'Surfboard shadow',
+ 'Crocodile',
+ 'Sea cow',
+ 'Stingray',
+ 'Person',
+ 'ocean',
+ 'Surfer',
+ 'Surfer',
+ 'Fish',
+ 'Killer whale',
+ 'Whale',
+ 'Dolphin',
+ 'Miscellaneous',
+ 'Unidentifiable shark',
+ 'Carpet shark',
+ 'Dusty shark',
+ 'Blue shark',
+ 'Great white shark',
+ 'Copper shark',
+ 'Nurse shark',
+ 'Silky shark',
+ 'Leopard shark',
+ 'Shortfin mako shark',
+ 'Hammerhead shark',
+ 'Oceanic whitetip shark',
+ 'Blacktip shark',
+ 'Tiger shark',
+ 'Bull shark']*3
+
+
+
+
+
+
+REPO_ID = "piperod91/australiapatrol"
+FILENAME = "mask2former"
+
+snapshot_download(repo_id=REPO_ID, token= os.environ.get('SHARK_MODEL'),local_dir='model/')
+
+
+
+
+# Choose to use a config and initialize the detector
+config_file ='model/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py'
+#'/content/mmdetection/configs/panoptic_fpn/panoptic-fpn_r50_fpn_ms-3x_coco.py'
+# Setup a checkpoint file to load
+checkpoint_file ='model/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic/checkpoint.pth'
+# '/content/drive/MyDrive/Algorithms/weights/shark_panoptic_weights_16_4_23/panoptic-fpn_r50_fpn_ms-3x_coco/epoch_36.pth'
+
+# register all modules in mmdet into the registries
+register_all_modules()
+
+# build the model from a config file and a checkpoint file
+model = init_detector(config_file, checkpoint_file, device='cuda:0')  # or device='cuda:0'
+model.dataset_meta['classes'] = classes
+# init visualizer(run the block only once in jupyter notebook)
+visualizer = VISUALIZERS.build(model.cfg.visualizer)
+# the dataset_meta is loaded from the checkpoint and
+# then pass to the model in init_detector
+visualizer.dataset_meta = model.dataset_meta
+def inference_frame(image):
+    result = inference_detector(model, image)
+    # show the results
+    visualizer.add_datasample(
+    'result',
+    image,
+    data_sample=result,
+    draw_gt = None,
+    show=False
+    )
+    frame = visualizer.get_image()
+    return frame