Add batch processing to Extras tab

This commit is contained in:
ArrowM 2022-09-15 22:23:37 -05:00 committed by AUTOMATIC1111
parent deea9f4d70
commit 3763837003
2 changed files with 68 additions and 44 deletions

View File

@ -13,66 +13,85 @@ import piexif.helper
cached_images = {} cached_images = {}
def run_extras(image, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility): def run_extras(image, image_folder, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
devices.torch_gc() devices.torch_gc()
existing_pnginfo = image.info or {} imageArr = []
image = image.convert("RGB") if image_folder != None:
info = "" if image != None:
print("Batch detected and single image detected, please only use one of the two. Aborting.")
return None
#convert file to pillow image
for img in image_folder:
image = Image.fromarray(np.array(Image.open(img)))
imageArr.append(image)
elif image != None:
if image_folder != None:
print("Batch detected and single image detected, please only use one of the two. Aborting.")
return None
else:
imageArr.append(image)
outpath = opts.outdir_samples or opts.outdir_extras_samples outpath = opts.outdir_samples or opts.outdir_extras_samples
if gfpgan_visibility > 0: for image in imageArr:
restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8)) existing_pnginfo = image.info or {}
res = Image.fromarray(restored_img)
if gfpgan_visibility < 1.0: image = image.convert("RGB")
res = Image.blend(image, res, gfpgan_visibility) info = ""
info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n" if gfpgan_visibility > 0:
image = res restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
res = Image.fromarray(restored_img)
if codeformer_visibility > 0: if gfpgan_visibility < 1.0:
restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight) res = Image.blend(image, res, gfpgan_visibility)
res = Image.fromarray(restored_img)
if codeformer_visibility < 1.0: info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"
res = Image.blend(image, res, codeformer_visibility) image = res
info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility)}\n" if codeformer_visibility > 0:
image = res restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
res = Image.fromarray(restored_img)
if upscaling_resize != 1.0: if codeformer_visibility < 1.0:
def upscale(image, scaler_index, resize): res = Image.blend(image, res, codeformer_visibility)
small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
pixels = tuple(np.array(small).flatten().tolist())
key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
c = cached_images.get(key) info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility)}\n"
if c is None: image = res
upscaler = shared.sd_upscalers[scaler_index]
c = upscaler.upscale(image, image.width * resize, image.height * resize)
cached_images[key] = c
return c if upscaling_resize != 1.0:
def upscale(image, scaler_index, resize):
small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
pixels = tuple(np.array(small).flatten().tolist())
key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n" c = cached_images.get(key)
res = upscale(image, extras_upscaler_1, upscaling_resize) if c is None:
upscaler = shared.sd_upscalers[scaler_index]
c = upscaler.upscale(image, image.width * resize, image.height * resize)
cached_images[key] = c
if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0: return c
res2 = upscale(image, extras_upscaler_2, upscaling_resize)
info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
res = Image.blend(res, res2, extras_upscaler_2_visibility)
image = res info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
res = upscale(image, extras_upscaler_1, upscaling_resize)
while len(cached_images) > 2: if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
del cached_images[next(iter(cached_images.keys()))] res2 = upscale(image, extras_upscaler_2, upscaling_resize)
info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
res = Image.blend(res, res2, extras_upscaler_2_visibility)
images.save_image(image, path=outpath, basename="", seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo) image = res
return image, plaintext_to_html(info), '' while len(cached_images) > 2:
del cached_images[next(iter(cached_images.keys()))]
images.save_image(image, path=outpath, basename="", seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo)
return imageArr, plaintext_to_html(info), ''
def run_pnginfo(image): def run_pnginfo(image):

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@ -644,8 +644,12 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Blocks(analytics_enabled=False) as extras_interface: with gr.Blocks(analytics_enabled=False) as extras_interface:
with gr.Row().style(equal_height=False): with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'): with gr.Column(variant='panel'):
with gr.Group(): with gr.Tabs():
image = gr.Image(label="Source", source="upload", interactive=True, type="pil") with gr.TabItem('Single Image'):
image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
with gr.TabItem('Batch Process'):
image_batch = gr.File(label="Batch Process", file_count="multiple", source="upload", interactive=True, type="file")
upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2) upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2)
@ -666,7 +670,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
submit = gr.Button('Generate', elem_id="extras_generate", variant='primary') submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
with gr.Column(variant='panel'): with gr.Column(variant='panel'):
result_image = gr.Image(label="Result") result_images = gr.Gallery(label="Result")
html_info_x = gr.HTML() html_info_x = gr.HTML()
html_info = gr.HTML() html_info = gr.HTML()
@ -674,6 +678,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
fn=run_extras, fn=run_extras,
inputs=[ inputs=[
image, image,
image_batch,
gfpgan_visibility, gfpgan_visibility,
codeformer_visibility, codeformer_visibility,
codeformer_weight, codeformer_weight,
@ -683,7 +688,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
extras_upscaler_2_visibility, extras_upscaler_2_visibility,
], ],
outputs=[ outputs=[
result_image, result_images,
html_info_x, html_info_x,
html_info, html_info,
] ]