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from threading import Thread | |
import gradio as gr | |
import torch | |
from PIL import Image | |
from transformers import PreTrainedModel # for type hint | |
from transformers import TextIteratorStreamer, AutoModelForCausalLM, AutoTokenizer # Moondream | |
from transformers import YolosImageProcessor, YolosForObjectDetection # YOLOS-small-300 | |
# --- YOLOS --- # | |
yolos_id = "hustvl/yolos-small-300" | |
yolos_processor: YolosImageProcessor = YolosImageProcessor.from_pretrained(yolos_id) | |
yolos_model: YolosForObjectDetection = YolosForObjectDetection.from_pretrained(yolos_id) | |
# --- Moondream --- # | |
# Moondream does not support the HuggingFace pipeline system, so we have to do it manually | |
moondream_id = "vikhyatk/moondream2" | |
moondream_revision = "2024-04-02" | |
moondream_tokenizer = AutoTokenizer.from_pretrained(moondream_id, revision=moondream_revision) | |
moondream_model: PreTrainedModel = AutoModelForCausalLM.from_pretrained( | |
moondream_id, trust_remote_code=True, revision=moondream_revision | |
) | |
moondream_model.eval() | |
def answer_question(img, prompt): | |
""" | |
Submits an image and prompt to the Moondream model. | |
:param img: | |
:param prompt: | |
:return: yields the output buffer string | |
""" | |
image_embeds = moondream_model.encode_image(img) | |
streamer = TextIteratorStreamer(moondream_tokenizer, skip_special_tokens=True) | |
thread = Thread( | |
target=moondream_model.answer_question, | |
kwargs={ | |
"image_embeds": image_embeds, | |
"question": prompt, | |
"tokenizer": moondream_tokenizer, | |
"streamer": streamer, | |
}, | |
) | |
thread.start() | |
buffer = "" | |
for new_text in streamer: | |
buffer += new_text | |
yield buffer.strip() | |
def detect_objects(img: Image.Image): | |
""" | |
Submits an image to the YOLOS-Small-300 model for object detection. | |
:param img: | |
:return: | |
""" | |
inputs = yolos_processor(img, return_tensors="pt") | |
outputs = yolos_model(**inputs) | |
target_sizes = torch.tensor([tuple(reversed(img.size))]) | |
results = yolos_processor.post_process_object_detection(outputs, threshold=0.7, target_sizes=target_sizes)[0] | |
box_images = [] | |
for score, label, box in zip(results["scores"], results["labels"], results["boxes"]): | |
box = [round(i, 2) for i in box.tolist()] | |
print( | |
f"Detected {yolos_model.config.id2label[label.item()]} with confidence " | |
f"{round(score.item(), 3)} at location {box}" | |
) | |
box_images.append(( | |
img.crop((box[0], box[1], box[2], box[3])), | |
f"{yolos_model.config.id2label[label.item()]} ({round(score.item(), 3)})") | |
) | |
box_images.append((img, f"original")) | |
return box_images | |
def get_selected_index(evt: gr.SelectData) -> int: | |
""" | |
Listener for the gallery selection event. | |
:return: index of the currently selected image | |
""" | |
return evt.index | |
def to_moondream(images: list[tuple[Image.Image, str | None]], index: int) -> tuple[gr.Tabs, Image.Image]: | |
""" | |
Listener that sends selected gallery image to the moondream model. | |
:param images: list of images from yolos_gallery | |
:param index: index of selected gallery image | |
:return: selected tab and selected image (no caption) | |
""" | |
return gr.Tabs(selected='moondream'), images[index][0] | |
def enable_button() -> gr.Button: | |
""" | |
Helper function for Gradio event listeners. | |
:return: a button with ``interactive=True`` and ``variant="primary"`` | |
""" | |
return gr.Button(interactive=True, variant="primary") | |
def disable_button() -> gr.Button: | |
""" | |
Helper function for Gradio event listeners. | |
:return: a button with ``interactive=False`` and ``variant="secondary"`` | |
""" | |
return gr.Button(interactive=False, variant="secondary") | |
if __name__ == "__main__": | |
with gr.Blocks() as app: | |
gr.Markdown( | |
""" | |
# Food Identifier | |
Final project for IAT 481 at Simon Fraser University, Spring 2024. | |
**Models used:** | |
- [hustvl/yolos-small-300](https://huggingface.co/hustvl/yolos-small-300) | |
- [vikhyatk/moondream2](https://huggingface.co/vikhyatk/moondream2) | |
""" | |
) | |
selected_image = gr.Number(visible=False, precision=0) | |
# Referenced: https://github.com/gradio-app/gradio/issues/7726#issuecomment-2028051431 | |
with gr.Tabs() as tabs: | |
with gr.Tab("Object Detection", id='yolos'): | |
with gr.Row(equal_height=False): | |
with gr.Column(): | |
yolos_submit = gr.Button("Detect Objects", interactive=False) | |
yolos_input = gr.Image(label="Input Image", type="pil", interactive=True, mirror_webcam=False) | |
with gr.Column(): | |
proceed_button = gr.Button("Select for Captioning", interactive=False) | |
yolos_gallery = gr.Gallery(label="Detected Objects", object_fit="scale-down", columns=3, | |
show_share_button=False, selected_index=None, allow_preview=False, | |
type="pil", interactive=False) | |
with gr.Tab("Captioning", id='moondream'): | |
with gr.Row(equal_height=False): | |
with gr.Column(): | |
with gr.Group(): | |
moon_prompt = gr.Textbox(label="Ask a question about the image:", | |
value="What is this food item? Include any text on labels.") | |
moon_submit = gr.Button("Submit", interactive=False) | |
moon_img = gr.Image(label="Image", type="pil", interactive=True, mirror_webcam=False) | |
moon_output = gr.TextArea(label="Answer", interactive=False) | |
# --- YOLOS --- # | |
yolos_input.upload(enable_button, None, yolos_submit) | |
yolos_input.clear(disable_button, None, yolos_submit) | |
yolos_submit.click(detect_objects, yolos_input, yolos_gallery) | |
yolos_gallery.select(get_selected_index, None, selected_image) | |
yolos_gallery.select(enable_button, None, proceed_button) | |
proceed_button.click(to_moondream, [yolos_gallery, selected_image], [tabs, moon_img]) | |
proceed_button.click(enable_button, None, moon_submit) | |
# --- Moondream --- # | |
moon_img.upload(enable_button, None, moon_submit) | |
moon_img.clear(disable_button, None, moon_submit) | |
moon_submit.click(answer_question, [moon_img, moon_prompt], moon_output) | |
app.queue().launch() | |