Advices

app.py

@@ -28,11 +28,11 @@ def check(
     prompt,
     negative_prompt,
     smooth_border,
-    denoising_steps,
     num_inference_steps,
     guidance_scale,
     image_guidance_scale,
     strength,
+    denoising_steps,
     randomize_seed,
     seed,
     debug_mode,
@@ -72,11 +72,11 @@ def uncrop(
     prompt,
     negative_prompt,
     smooth_border,
-    denoising_steps,
     num_inference_steps,
     guidance_scale,
     image_guidance_scale,
     strength,
+    denoising_steps,
     randomize_seed,
     seed,
     debug_mode,
@@ -90,11 +90,11 @@ def uncrop(
         prompt,
         negative_prompt,
         smooth_border,
-        denoising_steps,
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
         strength,
+        denoising_steps,
         randomize_seed,
         seed,
         debug_mode
@@ -120,9 +120,6 @@ def uncrop(
     if smooth_border is None:
         smooth_border = 0
 
-    if denoising_steps is None:
-        denoising_steps = 1000
-
     if num_inference_steps is None:
         num_inference_steps = 50
 
@@ -135,6 +132,9 @@ def uncrop(
     if strength is None:
         strength = 0.99
 
+    if denoising_steps is None:
+        denoising_steps = 1000
+
     if randomize_seed:
         seed = random.randint(0, max_64_bit_int)
 
@@ -315,11 +315,11 @@ with gr.Blocks() as interface:
         with gr.Accordion("Advanced options", open = False):
             negative_prompt = gr.Textbox(label = 'Negative prompt', placeholder = 'Describe what you do NOT want to see in the entire image', value = 'Border, frame, painting, scribbling, smear, noise, blur, watermark')
             smooth_border = gr.Slider(minimum = 0, maximum = 1024, value = 0, step = 2, label = "Smooth border", info = "lower=preserve original, higher=seamless")
-            denoising_steps = gr.Slider(minimum = 0, maximum = 1000, value = 1000, step = 1, label = "Denoising", info = "lower=irrelevant result, higher=relevant result")
             num_inference_steps = gr.Slider(minimum = 10, maximum = 100, value = 50, step = 1, label = "Number of inference steps", info = "lower=faster, higher=image quality")
             guidance_scale = gr.Slider(minimum = 1, maximum = 13, value = 7, step = 0.1, label = "Classifier-Free Guidance Scale", info = "lower=image quality, higher=follow the prompt")
             image_guidance_scale = gr.Slider(minimum = 1, value = 1.5, step = 0.1, label = "Image Guidance Scale", info = "lower=image quality, higher=follow the image")
-            strength = gr.Number(value = 0.99, minimum = 0.01, maximum = 1.0, step = 0.01, label = "Strength", info = "lower=follow the original area (discouraged), higher=redraw from scratch")
+            strength = gr.Slider(value = 0.99, minimum = 0.01, maximum = 1.0, step = 0.01, label = "Strength", info = "lower=follow the original area (discouraged), higher=redraw from scratch")
+            denoising_steps = gr.Number(minimum = 0, value = 1000, step = 1, label = "Denoising", info = "lower=irrelevant result, higher=relevant result")
             randomize_seed = gr.Checkbox(label = "\U0001F3B2 Randomize seed (not working, always checked)", value = True, info = "If checked, result is always different")
             seed = gr.Slider(minimum = 0, maximum = max_64_bit_int, step = 1, randomize = True, label = "Seed (if not randomized)")
             debug_mode = gr.Checkbox(label = "Debug mode", value = False, info = "Show intermediate results")
@@ -351,11 +351,11 @@ with gr.Blocks() as interface:
         prompt,
         negative_prompt,
         smooth_border,
-        denoising_steps,
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
         strength,
+        denoising_steps,
         randomize_seed,
         seed,
         debug_mode
@@ -369,11 +369,11 @@ with gr.Blocks() as interface:
         prompt,
         negative_prompt,
         smooth_border,
-        denoising_steps,
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
         strength,
+        denoising_steps,
         randomize_seed,
         seed,
         debug_mode
@@ -395,11 +395,11 @@ with gr.Blocks() as interface:
             prompt,
             negative_prompt,
             smooth_border,
-            denoising_steps,
             num_inference_steps,
             guidance_scale,
             image_guidance_scale,
             strength,
+            denoising_steps,
             randomize_seed,
             seed,
             debug_mode
@@ -421,11 +421,11 @@ with gr.Blocks() as interface:
                     "A woman, black hair, nowadays, in the street, ultrarealistic, realistic, photorealistic, 8k",
                     "Border, frame, painting, drawing, cartoon, scribbling, smear, noise, blur, watermark",
                     0,
-                    1000,
                     50,
                     7,
                     1.5,
                     0.99,
+                    1000,
                     True,
                     42,
                     False
@@ -439,11 +439,11 @@ with gr.Blocks() as interface:
                     "A man, jumping in the air, outside, ultrarealistic, realistic, photorealistic, 8k",
                     "Border, frame, painting, drawing, cartoon, scribbling, smear, noise, blur, watermark",
                     0,
-                    1000,
                     50,
                     7,
                     1.5,
                     0.99,
+                    1000,
                     True,
                     42,
                     False
@@ -457,11 +457,11 @@ with gr.Blocks() as interface:
                     "An old yellow car, in a town, ultrarealistic, realistic, photorealistic, 8k",
                     "Border, frame, painting, drawing, cartoon, scribbling, smear, noise, blur, watermark",
                     0,
-                    1000,
                     50,
                     7,
                     1.5,
                     0.99,
+                    1000,
                     True,
                     42,
                     False
@@ -469,5 +469,41 @@ with gr.Blocks() as interface:
             ],
         cache_examples = False,
     )
+    
+    gr.Markdown(
+        """
+        ## How to prompt your image
+
+        To easily read your prompt, start with the subject, then describ the pose or action, then secondary elements, then the background, then the graphical style, then the image quality:
+        ```
+        A Vietnamese woman, red clothes, walking, smilling, in the street, a car on the left, in a modern city, photorealistic, 8k
+        ```
+
+        You can use round brackets to increase the importance of a part:
+        ```
+        A Vietnamese woman, (red clothes), walking, smilling, in the street, a car on the left, in a modern city, photorealistic, 8k
+        ```
+
+        You can use several levels of round brackets to even more increase the importance of a part:
+        ```
+        A Vietnamese woman, ((red clothes)), (walking), smilling, in the street, a car on the left, in a modern city, photorealistic, 8k
+        ```
+
+        You can use number instead of several round brackets:
+        ```
+        A Vietnamese woman, (red clothes:1.5), (walking), smilling, in the street, a car on the left, in a modern city, photorealistic, 8k
+        ```
+
+        You can do the same thing with square brackets to decrease the importance of a part:
+        ```
+        A [Vietnamese] woman, (red clothes:1.5), (walking), smilling, in the street, a car on the left, in a modern city, photorealistic, 8k
+        ```
+
+        To easily read your negative prompt, organize it the same way as your prompt (not important for the AI):
+        ```
+        man, boy, hat, running, tree, bicycle, forest, drawing, painting, cartoon, 3d, monochrome, blurry, noisy, bokeh
+        ```
+        """
+    )
 
     interface.queue().launch()