Update app.py (#1)

- Update app.py (e219337a866fd2fa2178190f891d19c19a82574e)


Co-authored-by: Tokai Falco <Falco-TK@users.noreply.huggingface.co>

app.py

@@ -19,14 +19,48 @@ def generate_txt2img(prompt, is_negative=False, image_style="None style", steps=
     }
 
     if image_style == "Cinematic":
-        base_payload["inputs"] += ", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko"
-        base_payload["is_negative"] += ", abstract, cartoon, stylized"
+        payload[
+            "inputs"
+        ] += ", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko"
+        payload[
+            "is_negative"
+        ] += ", anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"
     elif image_style == "Digital Art":
-        base_payload["inputs"] += ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star"
-        base_payload["is_negative"] += ", sharp , modern , bright"
+        payload[
+            "inputs"
+        ] += ", faded, vintage, nostalgic, by Jose Villa, Elizabeth Messina, Ryan Brenizer, Jonas Peterson, Jasmine Star"
+        payload[
+            "is_negative"
+        ] += ", sharp , modern , bright, photo, photorealistic, realism, ugly"
     elif image_style == "Portrait":
-        base_payload["inputs"] += ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)"
-
+        payload[
+            "inputs"
+        ] += ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)"
+    elif image_style == "Photographic":
+        payload[
+            "inputs"
+        ] += ",cinematic photo, 35mm photograph, film, bokeh, professional, 4k, highly detailed"
+        payload["is_negative"] += (
+            ", drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
+        )
+    elif image_style == "Anime":
+        payload[
+            "inputs"
+        ] += "anime artwork,anime style, key visual, vibrant, studio anime, highly detailed"
+        payload[
+            "is_negative"
+        ] += ", photo, deformed, black and white, realism, disfigured, low contrast"
+
+    elif image_style == "Fantasy art":
+        payload[
+            "inputs"
+        ] += ", ethereal fantasy concept art, magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy"
+        payload[
+            "is_negative"
+        ] += "photographic, realistic, realism, 35mm film, dslr, cropped, frame, text, deformed, glitch, noise, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, sloppy, duplicate, mutated, black and white"
+
+    
+    
     image_bytes = requests.post(API_URL, headers=headers, json=base_payload).content
     image = Image.open(io.BytesIO(image_bytes))
     return image
@@ -121,7 +155,7 @@ with gr.Blocks(css=css) as demo:
             gr.Markdown("<h4>Advanced Settings</h4>")
             with gr.Accordion("Advanced Customizations", open=False):
                 negative_prompt = gr.Textbox(label="Negative Prompt (Optional)", placeholder="Example: blurry, unfocused", lines=2)
-                image_style = gr.Dropdown(label="Select Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], value="None style")
+                image_style = gr.Dropdown(label="Select Style", choices=["None style", "Cinematic", "Digital Art", "Portrait","Anime", "Fantasy art"], value="None style")
 
     with gr.Row():
         image_output = gr.Image(type="pil", label="Output Image")