File size: 10,236 Bytes
c49a0ab
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
import os
import unittest
import requests
import importlib

utils = importlib.import_module("extensions.sd-webui-controlnet.tests.utils", "utils")
from scripts.enums import StableDiffusionVersion
from modules import shared


class TestAlwaysonTxt2ImgWorking(unittest.TestCase):
    def setUp(self):
        self.sd_version = StableDiffusionVersion(
            int(
                os.environ.get(
                    "CONTROLNET_TEST_SD_VERSION", StableDiffusionVersion.SD1x.value
                )
            )
        )
        self.model = utils.get_model("canny", self.sd_version)

        controlnet_unit = {
            "enabled": True,
            "module": "none",
            "model": self.model,
            "weight": 1.0,
            "image": utils.readImage("test/test_files/img2img_basic.png"),
            "mask": utils.readImage("test/test_files/img2img_basic.png"),
            "resize_mode": 1,
            "lowvram": False,
            "processor_res": 64,
            "threshold_a": 64,
            "threshold_b": 64,
            "guidance_start": 0.0,
            "guidance_end": 1.0,
            "control_mode": 0,
            "pixel_perfect": False,
        }
        setup_args = [controlnet_unit] * getattr(self, "units_count", 1)
        self.setup_route(setup_args)

    def setup_route(self, setup_args):
        self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img"
        self.simple_txt2img = {
            "enable_hr": False,
            "denoising_strength": 0,
            "firstphase_width": 0,
            "firstphase_height": 0,
            "prompt": "example prompt",
            "styles": [],
            "seed": -1,
            "subseed": -1,
            "subseed_strength": 0,
            "seed_resize_from_h": -1,
            "seed_resize_from_w": -1,
            "batch_size": 1,
            "n_iter": 1,
            "steps": 3,
            "cfg_scale": 7,
            "width": 64,
            "height": 64,
            "restore_faces": False,
            "tiling": False,
            "negative_prompt": "",
            "eta": 0,
            "s_churn": 0,
            "s_tmax": 0,
            "s_tmin": 0,
            "s_noise": 1,
            "sampler_index": "Euler a",
            "alwayson_scripts": {},
        }
        self.setup_controlnet_params(setup_args)

    def setup_controlnet_params(self, setup_args):
        self.simple_txt2img["alwayson_scripts"]["ControlNet"] = {"args": setup_args}

    def assert_status_ok(self, msg=None, expected_image_num=None):
        msg = ("" if msg is None else msg) + f"\nPayload:\n{self.simple_txt2img}"

        resp = requests.post(self.url_txt2img, json=self.simple_txt2img)
        self.assertEqual(resp.status_code, 200, msg)
        # Note: Exception/error in ControlNet code likely will cause hook failure, which further leads
        # to detected map not being appended at the end of response image array.
        data = resp.json()
        if expected_image_num is None:
            expected_image_num = self.simple_txt2img["n_iter"] * self.simple_txt2img[
                "batch_size"
            ] + min(
                sum(
                    [
                        unit.get("save_detected_map", True)
                        for unit in self.simple_txt2img["alwayson_scripts"]["ControlNet"][
                            "args"
                        ]
                    ]
                ),
                shared.opts.data.get("control_net_unit_count", 3),
            )
        self.assertEqual(len(data["images"]), expected_image_num, msg)

    def test_txt2img_simple_performed(self):
        self.assert_status_ok()

    def test_txt2img_alwayson_scripts_default_units(self):
        self.units_count = 0
        self.setUp()
        self.assert_status_ok()

    def test_txt2img_multiple_batches_performed(self):
        self.simple_txt2img["n_iter"] = 2
        self.assert_status_ok()

    def test_txt2img_batch_performed(self):
        self.simple_txt2img["batch_size"] = 2
        self.assert_status_ok()

    def test_txt2img_2_units(self):
        self.units_count = 2
        self.setUp()
        self.assert_status_ok()

    def test_txt2img_8_units(self):
        self.units_count = 8
        self.setUp()
        self.assert_status_ok()

    def test_txt2img_default_params(self):
        self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
            {
                "input_image": utils.readImage("test/test_files/img2img_basic.png"),
                "model": self.model,
            }
        ]

        self.assert_status_ok()

    def test_call_with_preprocessors(self):
        available_modules = utils.get_modules()
        available_modules_list = available_modules.get("module_list", [])
        available_modules_detail = available_modules.get("module_detail", {})
        for module in ["depth", "openpose_full"]:
            assert module in available_modules_list, f"Failed to find {module}."
            assert (
                module in available_modules_detail
            ), f"Failed to find {module}'s detail."
            with self.subTest(module=module):
                self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
                    {
                        "input_image": utils.readImage(
                            "test/test_files/img2img_basic.png"
                        ),
                        "model": self.model,
                        "module": module,
                    }
                ]
                self.assert_status_ok(f"Running preprocessor module: {module}")

    def test_call_invalid_params(self):
        for param in ("processor_res", "threshold_a", "threshold_b"):
            with self.subTest(param=param):
                self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
                    {
                        "input_image": utils.readImage(
                            "test/test_files/img2img_basic.png"
                        ),
                        "model": self.model,
                        param: -1,
                    }
                ]
                self.assert_status_ok(f"Run with {param} = -1.")

    def test_save_detected_map(self):
        for save_map in (True, False):
            with self.subTest(save_map=save_map):
                self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
                    {
                        "input_image": utils.readImage(
                            "test/test_files/img2img_basic.png"
                        ),
                        "model": self.model,
                        "module": "depth",
                        "save_detected_map": save_map,
                    }
                ]

                resp = requests.post(self.url_txt2img, json=self.simple_txt2img).json()
                self.assertEqual(2 if save_map else 1, len(resp["images"]))

    def run_test_unit(
        self, module: str, model: str, sd_version: StableDiffusionVersion
    ) -> None:
        if self.sd_version != sd_version:
            return

        self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
            {
                "input_image": utils.readImage("test/test_files/img2img_basic.png"),
                "model": utils.get_model(model, sd_version),
                "module": module,
            }
        ]

        self.assert_status_ok()

    def test_ip_adapter_face(self):
        self.run_test_unit(
            "ip-adapter_clip_sdxl_plus_vith",
            "ip-adapter-plus-face_sdxl_vit-h",
            StableDiffusionVersion.SDXL,
        )
        self.run_test_unit(
            "ip-adapter_clip_sd15",
            "ip-adapter-plus-face_sd15",
            StableDiffusionVersion.SD1x,
        )

    def test_ip_adapter_fullface(self):
        self.run_test_unit(
            "ip-adapter_clip_sd15",
            "ip-adapter-full-face_sd15",
            StableDiffusionVersion.SD1x,
        )

    def test_control_lora(self):
        self.run_test_unit("canny", "sai_xl_canny_128lora", StableDiffusionVersion.SDXL)
        self.run_test_unit("canny", "control_lora_rank128_v11p_sd15_canny", StableDiffusionVersion.SD1x)

    def test_control_lllite(self):
        self.run_test_unit(
            "canny", "kohya_controllllite_xl_canny", StableDiffusionVersion.SDXL
        )

    def test_diffusers_controlnet(self):
        self.run_test_unit(
            "canny", "diffusers_xl_canny_small", StableDiffusionVersion.SDXL
        )

    def test_t2i_adapter(self):
        self.run_test_unit(
            "canny", "t2iadapter_canny_sd15v2", StableDiffusionVersion.SD1x
        )
        self.run_test_unit("canny", "t2i-adapter_xl_canny", StableDiffusionVersion.SDXL)

    def test_reference(self):
        self.run_test_unit("reference_only", "None", StableDiffusionVersion.SD1x)
        self.run_test_unit("reference_only", "None", StableDiffusionVersion.SDXL)

    def test_unrecognized_param(self):
        unit = self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"][0]
        unit["foo"] = True
        unit["is_ui"] = False
        self.assert_status_ok()

    def test_default_model(self):
        # Model "None" should be used when model is not specified in the payload.
        self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"] = [
            {
                "input_image": utils.readImage("test/test_files/img2img_basic.png"),
                "module": "reference_only",
            }
        ]
        self.assert_status_ok()
    
    def test_advanced_weighting(self):
        unit = self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"][0]
        unit["advanced_weighting"] = [0.75] * self.sd_version.controlnet_layer_num()
        self.assert_status_ok()

    def test_hr_option(self):
        # In non-hr run, hr_option should be ignored.
        unit = self.simple_txt2img["alwayson_scripts"]["ControlNet"]["args"][0]
        unit["hr_option"] = "High res only"
        self.assert_status_ok(expected_image_num=2)
        
        # Hr run.
        self.simple_txt2img["enable_hr"] = True
        self.assert_status_ok(expected_image_num=3)
        
        
if __name__ == "__main__":
    unittest.main()