fix blend image

app.py

@@ -5,29 +5,36 @@ from PIL import Image
 import qrcode
 from qrcode.constants import ERROR_CORRECT_H
 
-# ========= Stable Diffusion (prompt-only) =========
+# ========= device/dtype =========
 device = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
 dtype = torch.float16 if device != "cpu" else torch.float32
 
+# ========= SD 1.5 (prompt-only) =========
 sd_pipe = StableDiffusionPipeline.from_pretrained(
     "runwayml/stable-diffusion-v1-5",
     torch_dtype=dtype
 ).to(device)
 
-def sd_generate(prompt, steps, guidance, seed):
+def sd_generate(prompt, negative, steps, guidance, seed):
     gen = torch.Generator(device=device).manual_seed(int(seed)) if int(seed) != 0 else None
     def run():
-        return sd_pipe(prompt, num_inference_steps=int(steps), guidance_scale=float(guidance), generator=gen).images[0]
+        return sd_pipe(
+            prompt,
+            negative_prompt=negative or "",
+            num_inference_steps=int(steps),
+            guidance_scale=float(guidance),
+            generator=gen
+        ).images[0]
     if device in ("cuda", "mps"):
         with torch.autocast(device):
             return run()
     return run()
 
 # ========= QR Maker =========
-def make_qr(url: str = "http://www.mybirdfire.com", size: int = 512, border: int = 2) -> Image.Image:
+def make_qr(url: str = "http://www.mybirdfire.com", size: int = 512, border: int = 4) -> Image.Image:
     qr = qrcode.QRCode(
         version=None,
-        error_correction=ERROR_CORRECT_H,
+        error_correction=ERROR_CORRECT_H,  # highest EC
         box_size=10,
         border=border
     )
@@ -36,13 +43,14 @@ def make_qr(url: str = "http://www.mybirdfire.com", size: int = 512, border: int
     img = qr.make_image(fill_color="black", back_color="white").convert("RGB")
     return img.resize((size, size), resample=Image.NEAREST)
 
-# ========= ControlNet Stylizer (prompt + QR) =========
-# lazy-load to speed initial startup
-_cn_loaded = {"pipe": None}
+# ========= ControlNet Stylizer (SD1.5 + sd15-canny) =========
+_cn = {"pipe": None}
 def _load_controlnet():
-    if _cn_loaded["pipe"] is None:
+    if _cn["pipe"] is None:
         from diffusers import StableDiffusionControlNetPipeline, ControlNetModel
         from controlnet_aux import CannyDetector
+        from diffusers.schedulers.scheduling_euler_discrete import EulerDiscreteScheduler
+
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=dtype)
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
             "runwayml/stable-diffusion-v1-5",
@@ -50,16 +58,16 @@ def _load_controlnet():
             torch_dtype=dtype,
             safety_checker=None
         ).to(device)
+        # Use Euler to match your sampler preference
+        pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
         pipe.enable_attention_slicing()
         pipe.enable_vae_slicing()
-        _cn_loaded["pipe"] = pipe
-        _cn_loaded["canny"] = CannyDetector()
-    return _cn_loaded["pipe"], _cn_loaded["canny"]
-
-def stylize_qr(prompt: str, steps: int, guidance: float, seed: int, canny_low: int, canny_high: int):
-    # Always make QR from URL
-    qr_image = make_qr("http://www.mybirdfire.com", size=512, border=2)
+        _cn["pipe"] = pipe
+        _cn["canny"] = CannyDetector()
+    return _cn["pipe"], _cn["canny"]
 
+def stylize_qr(prompt: str, negative: str, steps: int, guidance: float, seed: int, canny_low: int, canny_high: int):
+    qr_image = make_qr("http://www.mybirdfire.com", size=512, border=4)
     pipe, canny = _load_controlnet()
     edges = canny(qr_image, low_threshold=int(canny_low), high_threshold=int(canny_high))
 
@@ -67,6 +75,7 @@ def stylize_qr(prompt: str, steps: int, guidance: float, seed: int, canny_low: i
     def run():
         return pipe(
             prompt=str(prompt),
+            negative_prompt=negative or "",
             image=edges,
             num_inference_steps=int(steps),
             guidance_scale=float(guidance),
@@ -79,32 +88,34 @@ def stylize_qr(prompt: str, steps: int, guidance: float, seed: int, canny_low: i
 
 # ========= UI =========
 with gr.Blocks() as demo:
-    gr.Markdown("## Stable Diffusion + QR Code + ControlNet (step by step)")
+    gr.Markdown("## Stable Diffusion + QR Code + ControlNet")
 
     with gr.Tab("Stable Diffusion (prompt → image)"):
         prompt = gr.Textbox(label="Prompt", value="A fantasy castle at sunset")
+        negative = gr.Textbox(label="Negative Prompt", value="lowres, bad anatomy, worst quality")
         steps  = gr.Slider(10, 50, value=30, label="Steps", step=1)
-        cfg    = gr.Slider(1, 12, value=7.5, label="Guidance Scale", step=0.1)
+        cfg    = gr.Slider(1, 12, value=7.0, label="Guidance Scale", step=0.1)
         seed   = gr.Number(value=0, label="Seed (0 = random)", precision=0)
         out_sd = gr.Image(label="Generated Image")
-        gr.Button("Generate").click(sd_generate, [prompt, steps, cfg, seed], out_sd)
+        gr.Button("Generate").click(sd_generate, [prompt, negative, steps, cfg, seed], out_sd)
 
     with gr.Tab("QR Maker (mybirdfire)"):
         url   = gr.Textbox(label="URL/Text", value="http://www.mybirdfire.com")
         size  = gr.Slider(256, 1024, value=512, step=64, label="Size (px)")
-        quiet = gr.Slider(0, 8, value=2, step=1, label="Border (quiet zone)")
+        quiet = gr.Slider(0, 8, value=4, step=1, label="Border (quiet zone)")
         out_qr = gr.Image(label="QR Code", type="pil")
         gr.Button("Generate QR").click(make_qr, [url, size, quiet], out_qr)
 
-    with gr.Tab("QR Stylizer (ControlNet)"):
-        s_prompt = gr.Textbox(label="Style Prompt", value="floral papercut style, high contrast, preserve sharp squares")
-        s_steps  = gr.Slider(10, 50, value=30, label="Steps", step=1)
-        s_cfg    = gr.Slider(1, 12, value=7.5, label="Guidance Scale", step=0.1)
-        s_seed   = gr.Number(value=0, label="Seed (0 = random)", precision=0)
-        canny_l  = gr.Slider(0, 255, value=100, step=1, label="Canny low")
-        canny_h  = gr.Slider(0, 255, value=200, step=1, label="Canny high")
+    with gr.Tab("QR Stylizer (ControlNet sd15-canny + Euler)"):
+        s_prompt = gr.Textbox(label="Style Prompt", value="Sky, Moon, Bird, Blue, In the dark, Goddess, Sweet")
+        s_negative = gr.Textbox(label="Negative Prompt", value="lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality, very displeasing, (bad)")
+        s_steps  = gr.Slider(10, 50, value=28, label="Steps", step=1)
+        s_cfg    = gr.Slider(1, 12, value=7.0, label="CFG", step=0.1)
+        s_seed   = gr.Number(value=1470713301, label="Seed", precision=0)
+        canny_l  = gr.Slider(0, 255, value=80, step=1, label="Canny low")
+        canny_h  = gr.Slider(0, 255, value=160, step=1, label="Canny high")
         out_styl = gr.Image(label="Stylized QR")
-        gr.Button("Stylize").click(stylize_qr, [s_prompt, s_steps, s_cfg, s_seed, canny_l, canny_h], out_styl)
+        gr.Button("Stylize").click(stylize_qr, [s_prompt, s_negative, s_steps, s_cfg, s_seed, canny_l, canny_h], out_styl)
 
 if __name__ == "__main__":
     demo.launch()