| import gradio as gr | |
| import requests | |
| API_URL = "https://api-inference.huggingface.co/models/Karim-Gamal/switch-base-8-finetuned-SemEval-2018-emojis-cen-2" | |
| headers = {"Authorization": "Bearer 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"} | |
| def query(payload): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| def sketch_recognition(text): | |
| output_temp = query({ | |
| "inputs": text, | |
| }) | |
| text_to_emoji = {'red' : '❤', 'face': '😍', 'joy':'😂', 'love':'💕', 'fire':'🔥', 'smile':'😊', 'sunglasses':'😎', 'sparkle':'✨', 'blue':'💙', 'kiss':'😘', 'camera':'📷', 'USA':'🇺🇸', 'sun':'☀' , 'purple':'💜', 'blink':'😉', 'hundred':'💯', 'beam':'😁', 'tree':'🎄', 'flash':'📸', 'tongue':'😜'} | |
| # Extract the dictionary from the list | |
| d = output_temp[0] | |
| # Extract the text from the 'generated_text' key | |
| text = d['generated_text'] | |
| return text_to_emoji[text.split(' ')[0]] | |
| # Split the text into individual words | |
| # pass# Implement your sketch recognition model here... | |
| gr.Interface(fn=sketch_recognition, inputs="text", outputs="text").launch() | |
| # gr.Interface.load("models/Karim-Gamal/switch-base-8-finetuned-SemEval-2018-emojis-cen-1").launch() |