feat(app): image_format call_input; support JXL

Author: gadicc

api/app.py

@@ -32,6 +32,8 @@
 from hashlib import sha256
 from threading import Timer
 import extras
+import jxlpy
+from jxlpy import JXLImagePlugin
 
 from diffusers import (
     StableDiffusionXLPipeline,
@@ -649,9 +651,11 @@ def callback(step: int, timestep: int, latents: torch.FloatTensor):
             }
 
     images_base64 = []
+    image_format = call_inputs.get("image_format", "PNG")
+    image_opts = { "lossless": True } if image_format == "PNG" else {}
     for image in images:
         buffered = BytesIO()
-        image.save(buffered, format="PNG")
+        image.save(buffered, format=image_format, **image_opts)
         images_base64.append(base64.b64encode(buffered.getvalue()).decode("utf-8"))
 
     await send("inference", "done", {"startRequestId": startRequestId}, send_opts)

requirements.txt

@@ -40,3 +40,4 @@ bitsandbytes==0.41.1       # was 0.40.2 until 2023-09-08
 
 invisible-watermark==0.2.0 # released 2023-07-06
 compel==2.0.2              # was 2.0.1 until 2023-09-08
+jxlpy==0.9.2               # added 2023-09-11