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Return json
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@ -105,12 +105,13 @@ def init():
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def get_all_images(db: Session = Depends(get_db)):
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from easydiffusion.easydb.mappings import Image
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images = db.query(Image).all()
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sum_string = "<div id='imagecontainer'>"
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for img in images:
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options = f"Path: {img.path}\nPrompt: {img.prompt}\nNegative Prompt: {img.negative_prompt}\nSeed: {img.seed}\nModel: {img.use_stable_diffusion_model}\nSize: {img.height}x{img.width}\nSampler: {img.sampler_name}\nSteps: {img.num_inference_steps}\nGuidance Scale: {img.guidance_scale}\nLoRA: {img.lora}\nUpscaling: {img.use_upscale}\nFace Correction: {img.use_face_correction}\n"
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sum_string += f"<img src='/image/{img.path}' title='{options}'>"
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sum_string += "</div>"
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return Response(content=sum_string, media_type="text/html")
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# sum_string = "<div id='imagecontainer'>"
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# for img in images:
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# options = f"Path: {img.path}\nPrompt: {img.prompt}\nNegative Prompt: {img.negative_prompt}\nSeed: {img.seed}\nModel: {img.use_stable_diffusion_model}\nSize: {img.height}x{img.width}\nSampler: {img.sampler_name}\nSteps: {img.num_inference_steps}\nGuidance Scale: {img.guidance_scale}\nLoRA: {img.lora}\nUpscaling: {img.use_upscale}\nFace Correction: {img.use_face_correction}\n"
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# sum_string += f"<img src='/image/{img.path}' title='{options}'>"
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# sum_string += "</div>"
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# return Response(content=sum_string, media_type="text/html")
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return images
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def get_filename_from_url(url):
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