Controlnet not working ┗( ▔, ▔ )┛

[Louis24]

api = webuiapi.WebUIApi()
api = webuiapi.WebUIApi(host="127.0.0.1", port=7860)

r = api.txt2img(
    prompt="photo of a beautiful girl with blonde hair", height=512,    enable_hr=True,
        hr_scale=2,
        seed=-1,)
img = r.image

r.image.save("img1.png")


# txt2img with ControlNet (used 1.0 but also supports 1.1)
unit1 = webuiapi.ControlNetUnit(
    input_image=img, module="canny", model="control_v11p_sd15_canny [d14c016b]"
)

# r = api.txt2img(prompt="photo of a beautiful girl", controlnet_units=[unit1])
r = api.txt2img(prompt="cake", controlnet_units=[unit1])
r.image.save("img2.png")

this one worked, but when the img comes from local disk It wont work

[Louis24]

{'prompt': 'cake, fruit, cream ,masterpiece, best quality, top quality, ultra highres, 8k hdr, 8k wallpaper', 'negative_prompt': 'lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry', 'styles': [], 'seed': -1, 'subseed': -1, 'subseed_strength': 0.0, 'seed_resize_from_h': 0, 'seed_resize_from_w': 0, 'sampler_name': 'DPM++ 2M Karras', 'batch_size': 1, 'n_iter': 1, 'steps': 20, 'cfg_scale': 7.0, 'width': 512, 'height': 512, 'restore_faces': False, 'tiling': False, 'do_not_save_samples': False, 'do_not_save_grid': False, 'eta': 1.0, 'denoising_strength': 0.7, 's_min_uncond': None, 's_churn': 0.0, 's_tmax': 0.0, 's_tmin': 0.0, 's_noise': 1.0, 'override_settings': {}, 'override_settings_restore_afterwards': True, 'refiner_checkpoint': None, 'refiner_switch_at': None, 'disable_extra_networks': False, 'comments': None, 'enable_hr': False, 'firstphase_width': 0, 'firstphase_height': 0, 'hr_scale': 2.0, 'hr_upscaler': 'Latent', 'hr_second_pass_steps': 0, 'hr_resize_x': 0, 'hr_resize_y': 0, 'hr_checkpoint_name': None, 'hr_sampler_name': None, 'hr_prompt': '', 'hr_negative_prompt': '', 'sampler_index': 
'Euler a', 'script_name': None, 'script_args': [], 'send_images': True, 'save_images': True, 'alwayson_scripts': {'ControlNet': {'args': [{'input_image': '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', 'mask': None, 'module': 'canny', 'model': 'control_v11p_sd15_canny [d14c016b]', 'weight': 1.0, 'resize_mode': 'Resize and Fill', 'lowvram': False, 'processor_res': 512, 'threshold_a': 64, 'threshold_b': 64, 'guidance': 1.0, 'guidance_start': 0.0, 'guidance_end': 1.0, 'control_mode': ['Balanced'], 'pixel_perfect': True, 'hr_option': 'Both'}]}}}

[Louis24]

{'prompt': 'cake, fruit, cream ,masterpiece, best quality, top quality, ultra highres, 8k hdr, 8k wallpaper', 'negative_prompt': 'lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry', 'styles': [], 'seed': -1, 'subseed': -1, 'subseed_strength': 0.0, 'seed_resize_from_h': 0, 'seed_resize_from_w': 0, 'sampler_name': 'DPM++ 2M Karras', 'batch_size': 1, 'n_iter': 1, 'steps': 20, 'cfg_scale': 7.0, 'width': 512, 'height': 512, 'restore_faces': False, 'tiling': False, 'do_not_save_samples': False, 'do_not_save_grid': False, 'eta': 1.0, 'denoising_strength': 0.7, 's_min_uncond': None, 's_churn': 0.0, 's_tmax': 0.0, 's_tmin': 0.0, 's_noise': 1.0, 'override_settings': {}, 'override_settings_restore_afterwards': True, 'refiner_checkpoint': None, 'refiner_switch_at': None, 'disable_extra_networks': False, 'comments': None, 'enable_hr': False, 'firstphase_width': 0, 'firstphase_height': 0, 'hr_scale': 2.0, 'hr_upscaler': 'Latent', 'hr_second_pass_steps': 0, 'hr_resize_x': 0, 'hr_resize_y': 0, 'hr_checkpoint_name': None, 'hr_sampler_name': None, 'hr_prompt': '', 'hr_negative_prompt': '', 'sampler_index':
'Euler a', 'script_name': None, 'script_args': [], 'send_images': True, 'save_images': True, 'alwayson_scripts': {'ControlNet': {'args': [{'input_image': 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lucmWDWEO3mp9X9O08/PzTbsXjMfjSqWifAyrs2XskJoTlxa3QOSYB6BMr9fL5/NbRrsj5tZOmrUs65dffrm8vMxmsw8fPkylUoZhtFqtT58+jUYjtRO8F5yJoqRNKSY+fvwYdRHwGQJAjdFolM/n1c65j8rvv/9uj0SMuiC7tuVSO5lM3r59u7OSOANgL0Z8unRI7+Uw/E/UBTgEs9nsyZMnB/Plvry8/Oc///nFbh0dHR0fH19cXER4CxWf/HYGQExmFCtxSO/lMBAAQVmWlc/nd7wW2+Hp9XqtVuvs7OzBgwdRLW4RkwBwjvefTCaH1KhIAMQNARDU8+fP7UVvoMRkMnny5MkBjHr0zZlDAhvisEv0AQRyenoa20tVMpnMZDKLfsvVB9iLCfd6vU6nE7dq5tnZmWmaMi9/s9nMsiz7veu6rut6TG5NgtvfycwHK+phSHus0WhEffbWSKfTV1dXXlfs6na7JycnsVqSc/fbhCncszMg56TZQ1qAk40h44YmIJ9ms9mLFy+iLsVnTNNsNpvdbrdQKHi9lKfT6VqtNh6PPc19DZXkIYPOtvJYpXJAh/ReDgMB4NPZ2VmserQqlUqj0Qi+pubJyUm73Y7DRk6771ePTwOFs1fp6dOn0RVEsR9//DHqIuAzrAXkh2VZX331lfJ283Q6XS6Xf/vtN0/DYDRNq9fra/eFtyzr9vZ2Mbz9w4cPdpntTfsSiYRhGKZprl74LMs6PT29vLz08zYU0TTN5c66qvR6vaOjo12+4ibpdHqxrbxlWd98880BdAMs7WOKWIi6DWovNZtN5Scil8stVkpxv4mHruvtdnupePb6BO5r8fYGv6uLNardS8SH8M/ksvh0OzvXIDqM1SBYByKGCAA/1PYWapq2+tsYDocnJyfbOwALhcJSZ+98Pq9UKv6uYrquX19fLxWj2WxG1W5rGEaY53C9tTdSkXD2gW/ajWCPmKa5aT0lRIhhoH78/fffvp9rD8rUdd1ebzmZTJqmuXqRTSaTtVotkUhYlrW64Iyu66tXhMlkcnx87LvpfDab5fP58/NzZ8U/m80Oh8PLy0vfHR7/+c9/7Dao2WzmaVmbSILnX//61y6XfNji06dPiz/rut5sNrfvShZnxWKxVqvF5+4KC/QB+HFzc5PP590/Pp1Om6b57NmzUOtxT548UTKHttvthlROe1PDd+/e3dzc3NuDYppmJANtnz9/vuMMsLvuHz9+vAjLx48fF4vFpb6Z2WzWarXev3/vKQaUz1JcW/nYJJPJPH78+AD2rTtYUd+C7KXpdOry481kMqtbBobBvl1QYgeDtYfD4b2NLbVaLexirDWdTsPeztNWKBR2sCFau91WWGbTNMMuMHaJAPDp3kqNPThnN4WZz+dqG0x2s3tfu93eNPLSMIxom4yvr6/D26feHuSzmzfivrLiRqlU2k2xsRs0Afk0mUyOjo62tIxv2bF9cVeu6vb8/fv3au/0s9ns48ePgx9H0zR7MNKmdoPRaHR8fLy6kOpSV0RU7A6YxVIZ9soZAScomKZ5fX3to0F8MBh0Oh2vi86q/W7oul4sFr/88kv3T8lms8lkMj5zLPCZqBNoj11fX2/6VFfr/uPxuFwuh1epjD/DMAqFwmrNdzgcLmVDnBcMCHiztWkwTLPZrFarjUZj7f+22+2YTM/2Tdf1nd0Qwz0CIJC1tdRisbj0sHK5vO8/YIWcMx5s8/m8WCym0+lUKlUul2M+XtB3l2YqlVp64/1+f2m6xuqXp9FoHMz4GdM02RY4VgiAoOr1uvP3mU6nl77ixWIxul9cTKXT6d10Myg3n899Z/nS3c/aGRvJZHLp5Q7m6m+jFyFWCAAF2u12oVDQNK1QKCxd/avVatS/uJjKZDIxr+mv5Xtk6lK71pYvhvNhCgd3xYSmaV6XqkV4CIAQKR+cc2DOz8+jPkWe+R4h6lyxYzweb6rXL90BxGFVPuX28bwfKlYDDVGQCbQSXFxc7NfnY09k8/FEwzCcl/Kzs7NN8+CcwbB2EvgBOMg3tacIgBC9e/cu6iLEmmVZ0S446tWbN2/8LQG7VJHfkiKHuh28k9eRrAgPARAWy7LYK/he79+/j7oIblmW9dtvv/l77tJl3eXazod6oTzU97WPCICw9Hq9A1jDPWx7dC148+aN7yq5c+DQ9pV8JNwBJPbqvB82AiAsfMXd2JdPybKsX3/91ffTnW9ze7XA2QdwwBUIJgbHBAEQln25tEXLsqy9qOcGqf4nPq/Lb7/2uX/k/mJoXHwQAGH566+/oi7Cfoh/Ugas/ic+f4+pVGrL3C5nJzMBgLARAGHZ/Z7me0r51srKBaz+JxKJ0Wi0eJu6rm9ZEsoZFQQAwkYAANsEr/7bbm5uFn9+9uzZlpdb/FnTtIO8Vu779paHhACIr0wms7rh+6rpdNpoNBQuNpfL5dws1NPtduOzg254glf/bc4hpIVCYdOVfTKZOG8CDnIm8M8//xx1EfBfCmYTY53t+7m74ebqv3B+fq7k+5BIJNwv0TMcDoO/XLPZ9PP57sSWNRt8cMbqlrWAnMsmd7tdVa8eE3Fe61sg7gDCErxp21OEfP311wFfzpZMJt1f8g61kXrh9PRUYReF8yagWCxuuglwTiBPp9MHtprsTz/9FHUR8P8IgPjyVPc8sEWD4+Dt27fOhvvgLi4uFkMDdF1/+fLl2ofd3t46U2ftqtF7qlQqsUF8rBAA8eWp6VnVqFNPL7oXQ/j9mc1mZ2dnao9pWdbp6enir6VSaW136Gw2e/Xq1eKvhmG02+3gLYqRK5fLrI4eO1G3QR2s4N13xWLRZXP8cDhUOFykUqm4edH5fH5ychL85eLZB6Dkra1Vq9UWr9JsNtc+ZnXRfHvTtJCKtIU9aNVpUxTZ2wXXarVms2lvfTOfz5v/xR4A8UQAhEXy9r+exDAA2u12eO9X13Xn1bBcLq99WCaTWd09cTgcNhqNcrlcKBSy2WxITUOpVKper2+pfIzH43q9bieBYRjFYvH6+jqcU4FwEQBhIQBcilsAzOfzsAeqL42E2XSzuLq96FrdbrfZbFYqlbXN64ZhlEql1Wq4PXr4/Px88eq6rhcKBU9jz7Dvvri7uwvxmy7Yixcv9muxeyV0Xbevno8fP04kEplMptPp/PXXX6PRaNPi2M1mM1ZheXFxobz1f9X19fVic7HRaHR8fLx2SQx7Loj7w04mk//93/+1dyIyDKNarbqcq9Hr9ZifJRABEJZ///vfr1+/jroUO5JMJk3TfPr06ZYxHpZlXVxc/Prrr0uLXHa73fhceizLevDgwQ46tw3D6Pf7i+l7g8Hghx9+WLv8p7+AbLVamUwmeBvRYDCYTCaTyWQwGNgH3HLYyWRyc3Pz6dMne8lrwzCePn0qYbbgHov6FuRgXV1dRX1uQ2cYRrlctnv8XBqPx84rgqZpsdoafpfDVEqlkvOlu93uav9qJpNZ+/ks+ldD+hzG43GpVFp7odd1ffWMX11dbUpxlw1ZiAQBEJbDm8PplE6nnRNWvWo0GvawpZOTE3UfeVDz+XyXa+/our5agGq1ajfKp9PparW6evWv1+ur8+8Mw6hUKpuus8PhcGneWSaTMU1zU3N/rVbbfuuw1OV77/CkTCbj74wgbARAiBSuzxMr944TtSuntVqtXC7XarVNFxpPtw47sPvM9lS8+Xy+fRaVpmmNRmPpWe12e9PVXNO0arXq/vELzhPaaDTcvNPVF0IcEAAhWvTyHQxd17dczSuVyqZ2gGQyGf9LwO5b7TwVz80cWsMwlkbc37tcx1I7kpvlPZyLGrls4k8mk/5PDEJDAITo+vrazW9jX2iattroPBwOS6WSy5YT0zTj3BxcqVTC/gyXuC9bvV53eUxn14Kbexrn412u7ucsmPv1oOI23hd3BEDY4jO+JbilKvx8Pi+VSl4PEucuwd1PtXVZME+dE6ZpLp64aaaxk7OB3mV7jrNs7gcaxaq/BzbWAgpXvV4/jJ4AwzCcqyNYlnV8fHxxceH1OL1e7/j4+IC3Ow+Dpz0J7CGYNjdXZ+fWdaGOf729vQ3v4PCHAAhXOp1uNpsHsJJXoVBwXk3Ozs46nY6/Q/V6vXw+H8OdIL/99tuoi7CG1y3JnBdxN/cNs9nM63XfOWfN/a3JaDRyhhPigAAIXTqd7vf719fXpmnu6d1AJpNxLlljWdabN2+CHLDVajkXvIyJWE1IXvC6JZnziuzyiV7D2Pl4T19p35UGhOQfURdAilwuZw8K6vV6dgPIpqURfPj777/fvHmjql0lm83aCznY0z4XqzssKNnv/uLi4uHDh+EtuumDvdSlknenio8diZ0B4PLKPhqNPO3tMxgMFje1qVTKfb3+w4cPsTrjIAB2bXExVVvf/PLLL5XUqXVdv7fnUNV9zNnZWTqdjtW2t9Vq9cmTJ1GX4v/52JHY+Xm6vDR7vQNwZuTDhw/dP5E7gLihCehAqJrC6ubinkwmlWSAZVn5fD5WHcKmabofcBk2H9X/RCLx6NGjxZ8/fvzo5imLjHF5Wp27D3nq3xoMBjHs+5GMAIAfqoa3TiaTFy9eKDmUKsVisdFouGkS0XU91E4dH9X/xOd3ll47XV2+HedhvQ5woB84VgiAA/Hhwwclx3FZH//xxx+VvFwikbi5uQnYpaycaZr9fn/LZrz2xObxePzzzz+HVIbJZOKj+p9MJhfRNZvNQrraOpuACIC9Rh+Aevbaub1e76+//trZ111Vl/JsNjs6Orq3Jqj2fZ2dnW3ZazASmqadn5+XSqVOp9PpdD5+/Khp2rfffqtpWi6XWxTVU9+pJ69fv/ZR/XcuFxHeuHt75Kjd6qhpmqeec1WbV0MJAkAly7Jev379yy+/RF2QQHZfR7Ms6/nz526WIdsxTdPsjXB3/LqtVsvfXdGzZ88Wf3737p26Ei3r9XqLsPEUALEaZAWagJTp9XpHR0f7fvWPSq/Xk7N/znaWZZ2envp4omEYzqzycVPofiiB71YgAiBWCABlXrx4wZc7iIuLCz7ARCJxeXnp73Nwrj7b6XTW7jG51uLGy/0dmHN80ffff+/yWYnPZxEjcgSAGjc3N/RuBeS75ntgfvvtN39PdLb//P777+6f6GMMsfPb7qkjxLKsHey4CZcIADVovlCi1Wrd3NxEXYootVotfzWJpfafsD/GIAOBuAmIDwJAgclkQvVfFeFR+scff/h7orP9p9VqhV3LtixrkQFe50NwBxAfBIACfKEV6vV6knsCfNeOnz59uviz1+7fRRuO1xWBFn/2dBMQq7nfwhEACnBLq9bbt2+jLkJk/H2XdF13tv/8+eefnp7ub/StMwA8JQcVpvggABTgC61WqAPYY87f3Y9pmouLuI8JwP4WkvI9EIjlgOKDAFCAW1q1JN9R+auMO1fm8FodWbr6u6/L+74DQHwQAArw7VdLcqD6Ww/D2f7jNT6X1vVzXwDnC3kqtqqVaxEcAaBArBaxOQCSA9XHMqu6rjs/Ma8NLEvfXvcfvnMvSU8/gbgt+CEZAaCA5AtWGFStNb2PPDWm25Z21PH66S29oqeNkRdhYy8J5/JZ/F7igwBQQNd17moV+umnn6IuglvKz3uhUPBaQXbuAJPwuF2Pvbip81+KxaL7AjhfyP3ObpIDPm4IADVevnwZdREORLFYjOfm7GsF2RBm7XMNw6hUKp6OUywWl/7F/QeYzWaXimEYhstte9PptPO59j7SPl4RUbqDCvP5nJ6A4EzTnM/nUZ9MD+bzue/LWS6X23RM9zcWhUJh9QjD4dBlM0u73V59+ng8dvP0Uqm09Kx7i61pWqPRUPLJQwkCQJlGo+HmJ4dNTk5Ooj6HfhQKBX/vt1qtbjqmy+9SMpmcTqdrj9Dtdu9NpmKxuKkA0+l0+/uqVCqrz2o2m1uaj3Rdr9frXj9ehIoAUKnZbNIZ4JWu66VSaTgcRn32fBoOhz6GtSSTye33OvfuTa/rerfb3XKEfr+/pUHfzc1Wo9Eol8umadq74pRKpXK53Gw2+/3+pqdcXV2tTizI5XL1en2/7u2EIAAUs6tOtHLeK5lMZrPZWq12ANeFbrfrvgs0kUhkMhk3gddutze1K2YymfF47KZs0+m0Wq3mcrlsNmuHQTabDbsm3u12m81ms9ncdIOCmPji7u5OzQ8anwtvS+59l8lkDnIk+GQyubm5effunT1AfmlRB3u79lQq9ezZM0+93Dc3N3/++edoNBoMBoZhpNPpR48eueynBbYjAABAKIaBAoBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACEUAAIBQBAAACPV/3LBISymg2fsAAAAASUVORK5CYII=', 'mask': None, 'module': 'canny', 'model': 'control_v11p_sd15_canny [d14c016b]', 'weight': 1.0, 'resize_mode': 'Resize and Fill', 'lowvram': False, 'processor_res': 512, 'threshold_a': 64, 'threshold_b': 64, 'guidance': 1.0, 'guidance_start': 0.0, 'guidance_end': 1.0, 'control_mode': ['Balanced'], 'pixel_perfect': True, 'hr_option': 'Both'}]}}}

[davidmartinrius]

api = webuiapi.WebUIApi()
api = webuiapi.WebUIApi(host="127.0.0.1", port=7860)

r = api.txt2img(
    prompt="photo of a beautiful girl with blonde hair", height=512,    enable_hr=True,
        hr_scale=2,
        seed=-1,)
img = r.image

r.image.save("img1.png")


# txt2img with ControlNet (used 1.0 but also supports 1.1)
unit1 = webuiapi.ControlNetUnit(
    input_image=img, module="canny", model="control_v11p_sd15_canny [d14c016b]"
)

# r = api.txt2img(prompt="photo of a beautiful girl", controlnet_units=[unit1])
r = api.txt2img(prompt="cake", controlnet_units=[unit1])
r.image.save("img2.png")

this one worked, but when the img comes from local disk It wont work

Hi, if you want to load an image from the disk you have to use PIL. In readme there is the documentation to load an image with PIL, like img2img examples.