forked from extern/easydiffusion
Round image sizes to a multiple of 8
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83c93eb9ef
commit
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@ -223,6 +223,8 @@ def generate_images_internal(
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if req.init_image is not None and not context.test_diffusers:
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if req.init_image is not None and not context.test_diffusers:
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req.sampler_name = "ddim"
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req.sampler_name = "ddim"
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req.width, req.height = map(lambda x: x - x % 8, (req.width, req.height)) # clamp to 8
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if req.control_image and task_data.control_filter_to_apply:
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if req.control_image and task_data.control_filter_to_apply:
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req.control_image = filter_images(context, req.control_image, task_data.control_filter_to_apply)[0]
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req.control_image = filter_images(context, req.control_image, task_data.control_filter_to_apply)[0]
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@ -1365,6 +1365,12 @@ function getCurrentUserRequest() {
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// numOutputsParallel = 1 // force 1 parallel
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// numOutputsParallel = 1 // force 1 parallel
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// }
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// }
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// clamp to multiple of 8
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let width = parseInt(widthField.value)
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let height = parseInt(heightField.value)
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width = width - (width % 8)
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height = height - (height % 8)
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const newTask = {
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const newTask = {
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batchesDone: 0,
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batchesDone: 0,
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numOutputsTotal: numOutputsTotal,
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numOutputsTotal: numOutputsTotal,
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@ -1377,8 +1383,8 @@ function getCurrentUserRequest() {
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num_outputs: numOutputsParallel,
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num_outputs: numOutputsParallel,
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num_inference_steps: parseInt(numInferenceStepsField.value),
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num_inference_steps: parseInt(numInferenceStepsField.value),
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guidance_scale: parseFloat(guidanceScaleField.value),
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guidance_scale: parseFloat(guidanceScaleField.value),
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width: parseInt(widthField.value),
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width: width,
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height: parseInt(heightField.value),
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height: height,
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// allow_nsfw: allowNSFWField.checked,
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// allow_nsfw: allowNSFWField.checked,
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vram_usage_level: vramUsageLevelField.value,
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vram_usage_level: vramUsageLevelField.value,
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sampler_name: samplerField.value,
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sampler_name: samplerField.value,
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