Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| from fastai.vision.all import * | |
| def get_headcount(filename): | |
| #print(filename) | |
| filename = str(filename) | |
| filename = filename.split("/")[-1] | |
| return df[df["Name"]==filename]["HeadCount"].values[0] | |
| learn = load_learner("export_facecount.pkl") | |
| # labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| op = learn.predict(img) | |
| return int(op[0][0]) | |
| title = "Face count" | |
| description = "A Car or Bike or not classifier trained with downloaded data from internet. Created as a demo for Gradio and HuggingFace Spaces." | |
| examples = ["conf.jpeg"] | |
| interpretation = "default" | |
| enable_queue = True | |
| gr.Interface( | |
| fn=predict, | |
| inputs=gr.inputs.Image(shape=(512, 512)), | |
| outputs=gr.outputs.Textbox(type="number", label="Number of faces"), | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| interpretation=interpretation, | |
| enable_queue=enable_queue, | |
| ).launch(share=False) | |