rdezwart commited on
Commit
698fd5a
·
1 Parent(s): 0a5c36c

Add captions to detected images gallery

Browse files
Files changed (1) hide show
  1. app.py +7 -4
app.py CHANGED
@@ -1,9 +1,9 @@
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  from threading import Thread
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- from PIL import Image
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  import gradio as gr
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  import torch
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- from transformers import PreTrainedModel, AutoImageProcessor # for type hint
 
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  from transformers import TextIteratorStreamer, AutoModelForCausalLM, AutoTokenizer # Moondream
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  from transformers import YolosImageProcessor, YolosForObjectDetection # YOLOS-small-300
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@@ -64,7 +64,10 @@ def detect_objects(img: Image.Image):
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  f"Detected {yolos_model.config.id2label[label.item()]} with confidence "
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  f"{round(score.item(), 3)} at location {box}"
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  )
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- box_images.append(img.crop((box[0], box[1], box[2], box[3])))
 
 
 
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  return box_images
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@@ -82,7 +85,7 @@ if __name__ == "__main__":
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  with gr.Tab("Object Detection"):
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  with gr.Row():
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  yolos_input = gr.Image(type="pil")
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- yolos_output = gr.Gallery(label="Detected Objects", show_label=True)
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  yolos_button = gr.Button("Submit")
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  with gr.Tab("Inference"):
 
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  from threading import Thread
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  import gradio as gr
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  import torch
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+ from PIL import Image
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+ from transformers import PreTrainedModel # for type hint
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  from transformers import TextIteratorStreamer, AutoModelForCausalLM, AutoTokenizer # Moondream
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  from transformers import YolosImageProcessor, YolosForObjectDetection # YOLOS-small-300
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  f"Detected {yolos_model.config.id2label[label.item()]} with confidence "
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  f"{round(score.item(), 3)} at location {box}"
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  )
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+ box_images.append((
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+ img.crop((box[0], box[1], box[2], box[3])),
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+ f"{yolos_model.config.id2label[label.item()]} ({round(score.item(), 3)})")
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+ )
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  return box_images
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  with gr.Tab("Object Detection"):
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  with gr.Row():
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  yolos_input = gr.Image(type="pil")
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+ yolos_output = gr.Gallery(label="Detected Objects", object_fit="scale-down", columns=3)
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  yolos_button = gr.Button("Submit")
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  with gr.Tab("Inference"):