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README.md

@@ -4,7 +4,7 @@ emoji: 🛕🛕
 colorFrom: green
 colorTo: blue
 sdk: gradio
-sdk_version: 4.41.0
+sdk_version: 4.42.0
 app_file: app.py
 pinned: false
 duplicated_from: Yntec/Diffusion80XX

app.py

@@ -6,7 +6,7 @@ import asyncio
 import os
 from threading import RLock
 lock = RLock()
-HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
+HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary.
 
 
 def load_fn(models):
@@ -29,6 +29,7 @@ num_models = 6
 max_images = 6
 inference_timeout = 300
 default_models = models[:num_models]
+MAX_SEED = 2**32-1
 
 
 def extend_choices(choices):
@@ -48,7 +49,7 @@ def random_choices():
 
 # https://huggingface.co/docs/api-inference/detailed_parameters
 # https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
-async def infer(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, timeout=inference_timeout):
+async def infer(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1, timeout=inference_timeout):
     from pathlib import Path
     kwargs = {}
     if height is not None and height >= 256: kwargs["height"] = height
@@ -56,9 +57,11 @@ async def infer(model_str, prompt, nprompt="", height=None, width=None, steps=No
     if steps is not None and steps >= 1: kwargs["num_inference_steps"] = steps
     if cfg is not None and cfg > 0: cfg = kwargs["guidance_scale"] = cfg
     noise = ""
-    rand = randint(1, 500)
-    for i in range(rand):
-        noise += " "
+    if seed >= 0: kwargs["seed"] = seed
+    else:
+        rand = randint(1, 500)
+        for i in range(rand):
+            noise += " "
     task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn,
                                prompt=f'{prompt} {noise}', negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
     await asyncio.sleep(0)
@@ -78,13 +81,13 @@ async def infer(model_str, prompt, nprompt="", height=None, width=None, steps=No
     return None
 
 
-def gen_fn(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None):
+def gen_fn(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1):
     if model_str == 'NA':
         return None
     try:
         loop = asyncio.new_event_loop()
         result = loop.run_until_complete(infer(model_str, prompt, nprompt,
-                                         height, width, steps, cfg, inference_timeout))
+                                         height, width, steps, cfg, seed, inference_timeout))
     except (Exception, asyncio.CancelledError) as e:
         print(e)
         print(f"Task aborted: {model_str}")
@@ -115,10 +118,13 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
                 txt_input = gr.Textbox(label='Your prompt:', lines=4)
                 neg_input = gr.Textbox(label='Negative prompt:', lines=1)
                 with gr.Accordion("Advanced", open=False, visible=True):
-                    width = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                    height = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                    steps = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                    cfg = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                    with gr.Row():
+                        width = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        height = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                    with gr.Row():
+                        steps = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
+                        cfg = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                        seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
             with gr.Row():
                 gen_button = gr.Button(f'Generate up to {int(num_models)} images in up to 3 minutes total', scale=3)
                 random_button = gr.Button(f'Random {int(num_models)} 🎲', variant='secondary', scale=1)
@@ -141,7 +147,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
 
         for m, o in zip(current_models, output):
             gen_event = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fn,
-                              inputs=[m, txt_input, neg_input, height, width, steps, cfg], outputs=[o])
+                              inputs=[m, txt_input, neg_input, height, width, steps, cfg, seed], outputs=[o])
             o.change(add_gallery, [o, m, gallery], [gallery])
             stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event])
 
@@ -159,10 +165,13 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
                 txt_input2 = gr.Textbox(label='Your prompt:', lines=4)
                 neg_input2 = gr.Textbox(label='Negative prompt:', lines=1)
                 with gr.Accordion("Advanced", open=False, visible=True):
-                    width2 = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                    height2 = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                    steps2 = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                    cfg2 = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                    with gr.Row():
+                        width2 = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        height2 = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                    with gr.Row():
+                        steps2 = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
+                        cfg2 = gr.Number(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                        seed2 = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
             num_images = gr.Slider(1, max_images, value=max_images, step=1, label='Number of images')
             with gr.Row():
                 gen_button2 = gr.Button('Generate', scale=2)
@@ -185,9 +194,9 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=CSS) as demo:
             img_i = gr.Number(i, visible = False)
             num_images.change(lambda i, n: gr.update(visible = (i < n)), [img_i, num_images], o)
             gen_event2 = gr.on(triggers=[gen_button2.click, txt_input2.submit],
-                               fn=lambda i, n, m, t1, t2, n1, n2, n3, n4: gen_fn(m, t1, t2, n1, n2, n3, n4) if (i < n) else None,
+                               fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5: gen_fn(m, t1, t2, n1, n2, n3, n4, n5) if (i < n) else None,
                                inputs=[img_i, num_images, model_choice2, txt_input2, neg_input2,
-                                       height2, width2, steps2, cfg2], outputs=[o])
+                                       height2, width2, steps2, cfg2, seed2], outputs=[o])
             o.change(add_gallery, [o, model_choice2, gallery2], [gallery2])
             stop_button2.click(lambda: gr.update(interactive=False), None, stop_button2, cancels=[gen_event2])