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Runtime error
| from PIL import Image, ImageDraw | |
| from helper import summarize_predictions_natural_language, render_results_in_image | |
| from transformers import pipeline | |
| from tokenizers import Tokenizer, Encoding | |
| from tokenizers import decoders | |
| from tokenizers import models | |
| from tokenizers import normalizers | |
| from tokenizers import pre_tokenizers | |
| from tokenizers import processors | |
| # Load object detection pipeline | |
| object_detection_pipe = pipeline("object-detection", model="facebook/detr-resnet-50") | |
| # Load text-to-speech pipeline | |
| tts_pipe = pipeline("text-to-speech", model="kakao-enterprise/vits-ljs") | |
| def get_predictions(uploaded_image): | |
| pil_image = Image.open(uploaded_image) | |
| # Perform object detection | |
| pipeline_output = object_detection_pipe(pil_image) | |
| processed_image = render_results_in_image(pil_image, pipeline_output) | |
| # Summarize predictions | |
| text = summarize_predictions_natural_language(pipeline_output) | |
| corrected_text = correct_text(text) | |
| # Generate audio from text | |
| narrated_text = tts_pipe(corrected_text) | |
| audio_data = narrated_text["audio"][0] | |
| sample_rate = narrated_text["sampling_rate"] | |
| return processed_image,corrected_text, (sample_rate, audio_data) #corrected_text | |
| def correct_text(text): | |
| # Rule-based correction | |
| # Example: "there are one horse" -> "there is one horse" | |
| if "there are one" in text: | |
| text = text.replace("there are one", "there is one") | |
| return text |