Add batch processing to Extras tab

1 files changed, 59 insertions, 40 deletions

diff --git a/modules/extras.py b/modules/extras.py
index e3c7d3e5..ffae7d67 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -13,66 +13,85 @@ import piexif.helper
 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()

 

-    existing_pnginfo = image.info or {}

+    imageArr = []

 

-    image = image.convert("RGB")

-    info = ""

+    if image_folder != None:

+        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

 

-    if gfpgan_visibility > 0:

-        restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))

-        res = Image.fromarray(restored_img)

+    for image in imageArr:

+        existing_pnginfo = image.info or {}

+

+        image = image.convert("RGB")

+        info = ""

+

+        if gfpgan_visibility > 0:

+            restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))

+            res = Image.fromarray(restored_img)

 

-        if gfpgan_visibility < 1.0:

-            res = Image.blend(image, res, gfpgan_visibility)

+            if gfpgan_visibility < 1.0:

+                res = Image.blend(image, res, gfpgan_visibility)

 

-        info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"

-        image = res

+            info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"

+            image = res

 

-    if codeformer_visibility > 0:

-        restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)

-        res = Image.fromarray(restored_img)

+        if codeformer_visibility > 0:

+            restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)

+            res = Image.fromarray(restored_img)

 

-        if codeformer_visibility < 1.0:

-            res = Image.blend(image, res, codeformer_visibility)

+            if codeformer_visibility < 1.0:

+                res = Image.blend(image, res, codeformer_visibility)

 

-        info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility)}\n"

-        image = res

+            info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility)}\n"

+            image = res

 

-    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

+        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

 

-            c = cached_images.get(key)

-            if c is None:

-                upscaler = shared.sd_upscalers[scaler_index]

-                c = upscaler.upscale(image, image.width * resize, image.height * resize)

-                cached_images[key] = c

+                c = cached_images.get(key)

+                if c is None:

+                    upscaler = shared.sd_upscalers[scaler_index]

+                    c = upscaler.upscale(image, image.width * resize, image.height * resize)

+                    cached_images[key] = c

 

-            return c

+                return c

 

-        info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"

-        res = upscale(image, extras_upscaler_1, upscaling_resize)

+            info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"

+            res = upscale(image, extras_upscaler_1, upscaling_resize)

 

-        if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:

-            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)

+            if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:

+                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

+            image = res

 

-    while len(cached_images) > 2:

-        del cached_images[next(iter(cached_images.keys()))]

+        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)

+        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 image, plaintext_to_html(info), ''

+    return imageArr, plaintext_to_html(info), ''

 

 

 def run_pnginfo(image):