upgraded novita_client to 0.5.0

README.md

@@ -4,7 +4,7 @@ emoji: 📈
 colorFrom: indigo
 colorTo: red
 sdk: gradio
-sdk_version: 4.15.0
+sdk_version: 4.19.2
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -7,7 +7,7 @@ import base64
 from io import BytesIO
 import PIL.Image
 from typing import Tuple
-from novita_client import NovitaClient, V3TaskResponseStatus
+from novita_client import NovitaClient, V3TaskResponseStatus, InstantIDControlnetUnit
 from time import time
 
 from style_template import styles
@@ -120,26 +120,26 @@ LORA_MODELS = [
 
 
 CONTROLNET_DICT = dict(
-	pose={
-		'model_name': 'controlnet-openpose-sdxl-1.0',
-		'strength': 1,
-		'preprocessor': 'openpose',
-	},
-	depth={
-		'model_name': 'controlnet-depth-sdxl-1.0',
-		'strength': 1,
-		'preprocessor': 'depth',
-	},
-	canny={
-		'model_name': 'controlnet-canny-sdxl-1.0',
-		'strength': 1,
-		'preprocessor': 'canny',
-	},
-	lineart={
-		'model_name': 'controlnet-softedge-sdxl-1.0',
-		'strength': 1,
-		'preprocessor': 'lineart',
-	},
+	pose=InstantIDControlnetUnit(
+		model_name='controlnet-openpose-sdxl-1.0',
+		strength=1,
+		preprocessor='openpose',
+	),
+	depth=InstantIDControlnetUnit(
+		model_name='controlnet-depth-sdxl-1.0',
+		strength=1,
+		preprocessor='depth',
+	),
+	canny=InstantIDControlnetUnit(
+		model_name='controlnet-canny-sdxl-1.0',
+		strength=1,
+		preprocessor='canny',
+	),
+	lineart=InstantIDControlnetUnit(
+		model_name='controlnet-softedge-sdxl-1.0',
+		strength=1,
+		preprocessor='lineart',
+	),
 )
 
 last_check = 0
@@ -309,62 +309,41 @@ def generate_image (
 			height = int(height * scaling)
 
 		(
-			CONTROLNET_DICT['pose']['strength'],
-			CONTROLNET_DICT['canny']['strength'],
-			CONTROLNET_DICT['depth']['strength'],
-			CONTROLNET_DICT['lineart']['strength'],
+			CONTROLNET_DICT['pose'].strength,
+			CONTROLNET_DICT['canny'].strength,
+			CONTROLNET_DICT['depth'].strength,
+			CONTROLNET_DICT['lineart'].strength,
 		) = [controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4]
 
-		face_image_uploaded, ref_image_uploaded = upload_assets_with_cache(client, [face_image_path, ref_image_path])
-
-		res = client._post('/v3/async/instant-id', {
-			'extra': {
-				'response_image_type': 'jpeg',
-			},
-			'model_name': f'{model_name}.safetensors',
-			'face_image_assets_ids': [face_image_uploaded],
-			'ref_image_assets_ids': [ref_image_uploaded],
-			'prompt': prompt,
-			'negative_prompt': negative_prompt,
-			'controlnet': {
-				'units': [CONTROLNET_DICT[name] for name in controlnet_selection if name in CONTROLNET_DICT],
-			},
-			'loras': [dict(
-				model_name=f'{name}.safetensors',
-				scale=1,
-			) for name in lora_selection],
-			'image_num': 1,
-			'steps': num_steps,
-			'seed': seed,
-			'guidance_scale': guidance_scale,
-			'sampler_name': scheduler,
-			'id_strength': identitynet_strength_ratio,
-			'adapter_strength': adapter_strength_ratio,
-			'width': width,
-			'height': height,
-		})
-
-		print('task_id:', res['task_id'])
-		def progress (x):
+		def progress_ (x):
 			global last_check
 			t = time()
 			if t > last_check + 5:
 				last_check = t
-				print('progress:', t, x.task.status)
-		final_res = client.wait_for_task_v3(res['task_id'], callback=progress)
-		if final_res is None or final_res.task.status == V3TaskResponseStatus.TASK_STATUS_FAILED:
-			raise RuntimeError(f'Novita task failed: {final_res and final_res.task.status}')
-		print('status:', final_res.task.status)
-		print('returned images:', final_res.images)
-
-		final_res.download_images()
+				print('progress:', t, x)
+
+		res = client.instant_id(
+			model_name=f'{model_name}.safetensors',
+			face_images=[face_image_path],
+			ref_images=[ref_image_path],
+			prompt=prompt,
+			negative_prompt=negative_prompt,
+			controlnets=[CONTROLNET_DICT[name] for name in controlnet_selection if name in CONTROLNET_DICT],
+			steps=num_steps,
+			seed=seed,
+			guidance_scale=guidance_scale,
+			sampler_name=scheduler,
+			id_strength=identitynet_strength_ratio,
+			adapter_strength=adapter_strength_ratio,
+			width=width,
+			height=height,
+			#response_image_type='jpeg',	# wait for novita_client 0.5.1 to fix this argument
+			callback=progress_,
+		)
 	except Exception as e:
 		raise gr.Error(f'Error: {e}')
 
-	#print('final_res:', final_res)
-	#print('final_res.images_encoded:', final_res.images_encoded)
-
-	image = PIL.Image.open(BytesIO(base64.b64decode(final_res.images_encoded[0])))
+	image = PIL.Image.open(BytesIO(base64.b64decode(res.images_encoded[0])))
 
 	return image, gr.update(visible=True)
 

requirements.txt

@@ -1,2 +1,2 @@
-novita_client==0.4.12
+novita_client==0.5.0
 gradio==4.15.0