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| ## https://medium.com/@sa.pieri.98/build-your-first-hugging-face-space-with-gradio-a-beginners-guide-14bc42d66887 | |
| import gradio as gr | |
| from transformers import pipeline | |
| #pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog") | |
| #pipeline = pipeline(task="image-classification", model="hg2001/autotrain-animals-vs-humans2-37846100283") | |
| #pipeline = pipeline("image-classification", model="lazyturtl/roomclassifier") | |
| pipeline = pipeline("image-classification", model="dima806/facial_emotions_image_detection") | |
| def predict(image): | |
| predictions = pipeline(image) | |
| return {p["label"]: p["score"] for p in predictions} | |
| gr.Interface( | |
| predict, | |
| inputs = gr.Image(label="Upload Any photo", type = "filepath"), | |
| outputs = gr.Label(num_top_classes=5), | |
| title="Show your face ?", | |
| ).launch(share="True") | |
| #inputs = gr.Image(sources=["webcam"], streaming=True), | |
| #sources=["upload", "webcam", "clipboard"] | |
| # inputs = gr.Image(), | |