added ability to either specify a raw path or a base64 encoded string of an image

image_classifier/__main__.py

@@ -1,7 +1,13 @@
 import argparse
+import base64
+
+from io import BytesIO
 from pathlib import Path
 from .inference import CAPTCHA
 
+from PIL import Image
+from simple_http_server import route, server
+
 def main():
 	parser = argparse.ArgumentParser("CAPTCHA", allow_abbrev=False)
 	parser.add_argument("--listen", action='store_true')
@@ -14,18 +20,26 @@ def main():
 
 	captcha = CAPTCHA( config=args.yaml, ckpt=args.ckpt, device=args.device )
 	if args.listen:
-		from simple_http_server import route, server
-
 		@route("/")
-		def inference( path, temperature=1.0 ):
+		def inference( b64, temperature=1.0 ):
-			return { "answer": captcha.inference( path=Path(path), temperature=args.temp ) }
+			image = Image.open(BytesIO(base64.b64decode(b64))).convert("RGB")
+			return { "answer": captcha.inference( image=image, temperature=args.temp ) }
 		server.start(port=args.port)
 	else:
 		parser = argparse.ArgumentParser("CAPTCHA", allow_abbrev=False)
-		parser.add_argument("path", type=Path)
+		parser.add_argument("--path", type=Path)
-		args2, unknown = parser.parse_known_args()
+		parser.add_argument("--base64", type=str)
+		parser.add_argument("--temp", type=float, default=1.0)
+		args, unknown = parser.parse_known_args()
 
-		answer = captcha.inference( path=args2.path, temperature=args.temp )
+		if args.path:
+			image = Image.open(args.path).convert('RGB')
+		elif args.base64:
+			image = Image.open(BytesIO(base64.b64decode(args.base64))).convert("RGB")
+		else:
+			raise "Specify a --path or --base64."
+
+		answer = captcha.inference( image=image, temperature=args.temp )
 		print("Answer:", answer)
 
 if __name__ == "__main__":

image_classifier/inference.py

@@ -1,21 +1,24 @@
 import torch
 
-from PIL import Image
 import torchvision.transforms as transforms
 
 from .config import cfg
 from .export import load_models
+from .data import get_symmap, _get_symbols
 
 class CAPTCHA():
 	def __init__( self, width=300, height=80, config=None, ckpt=None, device="cuda", dtype="float32" ):
 		self.loading = True 
 		self.device = device
 		
+		if config:
+			cfg.load_yaml( config )
+
 		if ckpt:
 			self.load_model_from_ckpt( ckpt )
 		else:
 			self.load_model_from_cfg( config )
-
+		
 		self.model.eval()
 
 		self.width = width
@@ -34,8 +37,6 @@ class CAPTCHA():
 		self.model = torch.load(self.ckpt).to(self.device)
 
 	def load_model_from_cfg( self, config_path ):
-		if config_path:
-			cfg.load_yaml( config_path )
 
 		models = load_models()
 		for name in models:
@@ -43,8 +44,9 @@ class CAPTCHA():
 			self.model = model.to(self.device)
 			break
 
-	def inference( self, path, temperature=1.0 ):
+	def inference( self, image, temperature=1.0 ):
-		image = self.transform(Image.open(path).convert('RGB')).to(self.device)
+		image = self.transform(image).to(self.device)
+
 		answer = self.model( image=[image], sampling_temperature=temperature )
 		answer = answer[0].replace('<s>', "").replace("</s>", "")