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| import gradio as gr | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| from urllib.request import urlretrieve | |
| # get image examples from github | |
| urlretrieve("https://github.com/SamDaaLamb/ValorantTracker/blob/main/clip2_-1450-_jpg.jpg?raw=true", "clip2_-1450-_jpg.jpg") # make sure to use "copy image address when copying image from Github" | |
| urlretrieve("https://github.com/SamDaaLamb/ValorantTracker/blob/main/clip2_-539-_jpg.jpg?raw=true", "clip2_-539-_jpg.jpg") | |
| examples = [ # need to manually delete cache everytime new examples are added | |
| ["clip2_-1450-_jpg.jpg"], | |
| ["clip2_-539-_jpg.jpg"]] | |
| def speclab(img): | |
| # initialize the model | |
| model = torch.hub.load('SamDaLamb/ValorantTracker', 'best.pt', force_reload=True) # for some reasons loads the model in src rather than demo | |
| model.eval() | |
| # preprocess image to be used as input | |
| transforms = A.Compose([ | |
| A.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5)), | |
| ToTensorV2() | |
| ]) | |
| input = transforms(image=img)['image'] | |
| input = input.unsqueeze(0) | |
| # model prediction | |
| output = model(input) | |
| # overlay output onto original image | |
| img[output==255] = [0, 255, 0] | |
| return img | |
| # define app features and run | |
| title = "SpecLab Demo" | |
| description = "<p style='text-align: center'>Gradio demo for an ASPP model architecture trained on the SpecLab dataset. To use it, simply add your image, or click one of the examples to load them. Since this demo is run on CPU only, please allow additional time for processing. </p>" | |
| article = "<p style='text-align: center'><a href='https://github.com/Nano1337/SpecLab'>Github Repo</a></p>" | |
| css = "#0 {object-fit: contain;} #1 {object-fit: contain;}" | |
| demo = gr.Interface(fn=speclab, | |
| title=title, | |
| description=description, | |
| article=article, | |
| inputs=gr.Image(elem_id=0, show_label=False), | |
| outputs=gr.Image(elem_id=1, show_label=False), | |
| css=css, | |
| examples=examples, | |
| cache_examples=True, | |
| allow_flagging='never') | |
| demo.launch() |