clamp API params, limit filename length, remove queueing thing

api/serve.py

@@ -14,19 +14,21 @@ from io import BytesIO
 from os import environ, path, makedirs
 
 # defaults
-empty_prompt = "a photo of an astronaut eating a hamburger"
+default_prompt = "a photo of an astronaut eating a hamburger"
+default_height = 512
+default_width = 512
+default_steps = 20
+default_cfg = 8
+
 max_height = 512
 max_width = 512
-max_steps = 50
-max_cfg = 8
+max_steps = 150
+max_cfg = 30
 
 # paths
 model_path = environ.get('ONNX_WEB_MODEL_PATH', "../../stable_diffusion_onnx")
 output_path = environ.get('ONNX_WEB_OUTPUT_PATH', "../../web_output")
 
-# queue
-image_queue = set()
-
 # schedulers
 scheduler_list = {
   'ddpm': DDPMScheduler.from_pretrained(model_path, subfolder="scheduler"),
@@ -38,14 +40,23 @@ scheduler_list = {
   'dpm-multi': DPMSolverMultistepScheduler.from_pretrained(model_path, subfolder="scheduler"),
 }
 
-def setup():
-  if not path.exists(model_path):
-    raise RuntimeError('model path must exist')
-  if not path.exists(output_path):
-    makedirs(output_path)
+def get_and_clamp(args, key, default_value, max_value, min_value=1):
+  return min(max(int(args.get(key, default_value)), min_value), max_value)
+
+def get_from_map(args, key, values, default):
+  selected = args.get(key, default)
+  if selected in values:
+    return values[selected]
+  else:
+    return values[default]
 
 # setup
-setup()
+if not path.exists(model_path):
+  raise RuntimeError('model path must exist')
+
+if not path.exists(output_path):
+  makedirs(output_path)
+
 app = Flask(__name__)
 
 # routes
@@ -55,19 +66,16 @@ def hello():
 
 @app.route('/txt2img')
 def txt2img():
-  if len(image_queue) > 0:
-    return 'Queue full: %s' % (image_queue)
-
   user = request.remote_addr
-  prompt = request.args.get('prompt', empty_prompt)
-  height = request.args.get('height', max_height)
-  width = request.args.get('width', max_width)
-  steps = int(request.args.get('steps', max_steps))
-  cfg = int(request.args.get('cfg', max_cfg))
-  scheduler = scheduler_list[request.args.get('scheduler', 'euler-a')]
+
+  cfg = get_and_clamp(request.args, 'cfg', default_cfg, max_cfg)
+  height = get_and_clamp(request.args, 'height', default_height, max_height)
+  prompt = request.args.get('prompt', default_prompt)
+  steps = get_and_clamp(request.args, 'steps', default_steps, max_steps)
+  scheduler = get_from_map(request.args, 'scheduler', scheduler_list, 'euler-a')
+  width = get_and_clamp(request.args, 'width', default_width, max_width)
 
   print("txt2img from %s: %s/%s, %sx%s, %s" % (user, cfg, steps, width, height, prompt))
-  image_queue.add(user)
 
   pipe = OnnxStableDiffusionPipeline.from_pretrained(
     model_path,
@@ -83,7 +91,7 @@ def txt2img():
     guidance_scale=cfg
   ).images[0]
 
-  output = '%s/txt2img_%s.png' % (output_path, spinalcase(prompt))
+  output = '%s/txt2img_%s.png' % (output_path, spinalcase(prompt[0:64]))
   print("txt2img output: %s" % (output))
   image.save(output)
 
@@ -91,8 +99,6 @@ def txt2img():
   image.save(img_io, 'PNG', quality=100)
   img_io.seek(0)
 
-  image_queue.remove(user)
-
   res = make_response(send_file(img_io, mimetype='image/png'))
   res.headers.add('Access-Control-Allow-Origin', '*')
   return res