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import os
import shutil
import subprocess
# Clone the repository if not already present
if not os.path.exists("edge_vlm"):
subprocess.run(["git", "clone", "https://huggingface.co/irotem98/edge_vlm"])
# Install the required dependencies
subprocess.run(["pip", "install", "-r", "edge_vlm/requirements.txt"])
# Copy all files from edge_vlm to the current directory
source_dir = "edge_vlm"
destination_dir = "."
for filename in os.listdir(source_dir):
source_file = os.path.join(source_dir, filename)
destination_file = os.path.join(destination_dir, filename)
# Copy files, skipping directories like .git
if os.path.isfile(source_file):
shutil.copy(source_file, destination_file)
# Now import the model from the copied files
from model import MoondreamModel
import torch
import gradio as gr
# Load the model and tokenizer
model = MoondreamModel.load_model()
tokenizer = MoondreamModel.load_tokenizer()
# Define the default question
default_question = "Describe the image."
# Function to handle image and return generated caption
def generate_caption_with_default(image):
# Preprocess the image
preprocessed_image = MoondreamModel.preprocess_image(image)
# Generate caption
caption = MoondreamModel.generate_caption(model, preprocessed_image, tokenizer)
return caption
# Create Gradio interface
interface = gr.Interface(
fn=generate_caption_with_default,
inputs=gr.inputs.Image(type="pil", label="Upload an Image"),
outputs="text",
title="Image Caption Generator",
description=f"The default question is: '{default_question}'. Upload an image to generate a description."
)
# Launch the interface
interface.launch()
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