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TachibanaYoshino / AnimeGANv2

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime
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Inference with pre-trained model and sample data is not working. #69

Open jeongchanKim opened 12 months ago

jeongchanKim commented 12 months ago

I tried to test the inference with ubuntu environment. I used the pre-trained model and the sample data(HR_photo). But I cannot generate well. Some generated images are black, and some looks almost noise.

This is what I set from conda environment. Is there any missing or mismatched library version?

Name Version Build Channel

_libgcc_mutex 0.1 main _openmp_mutex 5.1 1_gnu _tflow_select 2.1.0 gpu absl-py 1.4.0 pypi_0 pypi astor 0.8.1 pypi_0 pypi blas 1.0 mkl bzip2 1.0.8 h7b6447c_0 c-ares 1.19.0 h5eee18b_0 ca-certificates 2023.05.30 h06a4308_0 cached-property 1.5.2 pypi_0 pypi cairo 1.16.0 hb05425b_5 certifi 2021.5.30 py36h06a4308_0 colorama 0.4.4 pyhd3eb1b0_0 cudatoolkit 10.0.130 0 cudnn 7.6.5 cuda10.0_0 cupti 10.0.130 0 dataclasses 0.8 pypi_0 pypi expat 2.5.0 h6a678d5_0 ffmpeg 4.0 hcdf2ecd_0 fontconfig 2.14.1 h4c34cd2_2 freeglut 3.0.0 hf484d3e_5 freetype 2.12.1 h4a9f257_0 gast 0.2.2 pypi_0 pypi glib 2.69.1 h4ff587b_1 google-pasta 0.2.0 pyhd3eb1b0_0 graphite2 1.3.14 h295c915_1 grpcio 1.48.2 pypi_0 pypi h5py 3.1.0 pypi_0 pypi harfbuzz 1.8.8 hffaf4a1_0 hdf5 1.10.2 hba1933b_1 icu 58.2 he6710b0_3 importlib-metadata 4.8.3 pypi_0 pypi intel-openmp 2022.1.0 h9e868ea_3769 jasper 2.0.14 hd8c5072_2 jpeg 9e h5eee18b_1 keras-applications 1.0.8 py_1 keras-preprocessing 1.1.2 pyhd3eb1b0_0 ld_impl_linux-64 2.38 h1181459_1 lerc 3.0 h295c915_0 libdeflate 1.17 h5eee18b_0 libffi 3.3 he6710b0_2 libgcc-ng 11.2.0 h1234567_1 libgfortran-ng 7.5.0 ha8ba4b0_17 libgfortran4 7.5.0 ha8ba4b0_17 libglu 9.0.0 hf484d3e_1 libgomp 11.2.0 h1234567_1 libopencv 3.4.2 hb342d67_1 libopus 1.3.1 h7b6447c_0 libpng 1.6.39 h5eee18b_0 libprotobuf 3.17.2 h4ff587b_1 libstdcxx-ng 11.2.0 h1234567_1 libtiff 4.5.1 h6a678d5_0 libuuid 1.41.5 h5eee18b_0 libvpx 1.7.0 h439df22_0 libwebp-base 1.2.4 h5eee18b_1 libxcb 1.15 h7f8727e_0 libxml2 2.10.4 hcbfbd50_0 lz4-c 1.9.4 h6a678d5_0 markdown 3.3.7 pypi_0 pypi mkl 2020.2 256 mkl-service 2.3.0 py36he8ac12f_0 mkl_fft 1.3.0 py36h54f3939_0 mkl_random 1.1.1 py36h0573a6f_0 ncurses 6.4 h6a678d5_0 numpy 1.19.5 pypi_0 pypi numpy-base 1.19.2 py36hfa32c7d_0 opencv 3.4.2 py36h6fd60c2_1 openssl 1.1.1v h7f8727e_0 opt_einsum 3.3.0 pyhd3eb1b0_1 pcre 8.45 h295c915_0 pip 21.2.2 py36h06a4308_0 pixman 0.40.0 h7f8727e_1 protobuf 3.19.6 pypi_0 pypi py-opencv 3.4.2 py36hb342d67_1 pyserial 3.5 py36h06a4308_0 python 3.6.13 h12debd9_1 readline 8.2 h5eee18b_0 scipy 1.5.2 py36h0b6359f_0 setuptools 58.0.4 py36h06a4308_0 six 1.16.0 pyhd3eb1b0_1 sqlite 3.41.2 h5eee18b_0 tensorboard 1.15.0 pyhb230dea_0 tensorflow 1.15.0 gpu_py36h5a509aa_0 tensorflow-base 1.15.0 gpu_py36h9dcbed7_0 tensorflow-estimator 1.15.1 pyh2649769_0 tensorflow-gpu 1.15.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi tk 8.6.12 h1ccaba5_0 tqdm 4.63.0 pyhd3eb1b0_0 typing-extensions 4.1.1 pypi_0 pypi webencodings 0.5.1 py36_1 werkzeug 2.0.3 pypi_0 pypi wheel 0.37.1 pyhd3eb1b0_0 wrapt 1.15.0 pypi_0 pypi xz 5.4.2 h5eee18b_0 zipp 3.6.0 pypi_0 pypi zlib 1.2.13 h5eee18b_0 zstd 1.5.5 hc292b87_0

jeongchanKim commented 12 months ago

1 (40)

This is what I got from HR_photo 1(40).jpg

Most of the results are same.

jeongchanKim commented 12 months ago

This log is what I run for inference.

checkpoint/generator_Hayao_weight/ WARNING:tensorflow:From test.py:39: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING:tensorflow:From test.py:41: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.

WARNING:tensorflow: The TensorFlow contrib module will not be included in TensorFlow 2.0. For more information, please see:

WARNING:tensorflow:From /home/jc-kim/anaconda3/envs/animeganv2/lib/python3.6/site-packages/tensorflow_core/contrib/layers/python/layers/layers.py:1057: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use layer.__call__ method instead. WARNING:tensorflow:From /home/jc-kim/jckim/AnimeGANv2/net/generator.py:41: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.

WARNING:tensorflow:From /home/jc-kim/jckim/AnimeGANv2/net/generator.py:58: The name tf.image.resize_images is deprecated. Please use tf.image.resize instead.

WARNING:tensorflow:From test.py:43: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.

WARNING:tensorflow:From test.py:45: The name tf.GPUOptions is deprecated. Please use tf.compat.v1.GPUOptions instead.

WARNING:tensorflow:From test.py:46: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

WARNING:tensorflow:From test.py:46: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

2023-09-12 10:56:09.931424: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA 2023-09-12 10:56:09.936578: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3699800000 Hz 2023-09-12 10:56:09.936918: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56446be0b050 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2023-09-12 10:56:09.936935: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2023-09-12 10:56:09.938045: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2023-09-12 10:56:10.001288: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.001452: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56446d886270 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2023-09-12 10:56:10.001463: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 3080, Compute Capability 8.6 2023-09-12 10:56:10.001551: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.001648: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: NVIDIA GeForce RTX 3080 major: 8 minor: 6 memoryClockRate(GHz): 1.71 pciBusID: 0000:2b:00.0 2023-09-12 10:56:10.001836: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2023-09-12 10:56:10.002618: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2023-09-12 10:56:10.003291: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2023-09-12 10:56:10.003482: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2023-09-12 10:56:10.004285: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2023-09-12 10:56:10.004958: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2023-09-12 10:56:10.006899: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2023-09-12 10:56:10.006943: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.007048: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.007117: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2023-09-12 10:56:10.007139: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2023-09-12 10:56:10.007300: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2023-09-12 10:56:10.007307: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2023-09-12 10:56:10.007310: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2023-09-12 10:56:10.007362: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.007459: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2023-09-12 10:56:10.007544: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9294 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:2b:00.0, compute capability: 8.6) [] Success to read checkpoint/generator_Hayao_weight/Hayao-99.ckpt 0%| | 0/45 [00:00<?, ?it/s]2023-09-12 10:57:17.122270: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2023-09-12 10:58:11.942482: W tensorflow/stream_executor/cuda/redzone_allocator.cc:312] Not found: ./bin/ptxas not found Relying on driver to perform ptx compilation. This message will be only logged once. 2023-09-12 10:58:11.954097: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 60%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 27/45 [01:04<00:04, 4.09it/s]2023-09-12 10:58:21.565655: W tensorflow/core/common_runtime/bfc_allocator.cc:305] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. /home/jc-kim/jckim/AnimeGANv2/tools/adjust_brightness.py:25: RuntimeWarning: divide by zero encountered in double_scalars brightness_difference = brightness1 / brightness2 /home/jc-kim/jckim/AnimeGANv2/tools/adjust_brightness.py:33: RuntimeWarning: invalid value encountered in multiply dstf = dst brightness_difference 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 45/45 [01:08<00:00, 1.52s/it] test-time: 68.44015574455261 s one image test time : 1.5208923498789468 s

jeongchanKim commented 12 months ago

Oh I got this log also, after uncomment the stats_graph(tf.get_default_graph()) in test.py

Use tf.compat.v1.graph_util.tensor_shape_from_node_def_name 125 ops no flops stats due to incomplete shapes. Parsing Inputs... Incomplete shape.

=========================Options============================= -max_depth 10000 -min_bytes 0 -min_peak_bytes 0 -min_residual_bytes 0 -min_output_bytes 0 -min_micros 0 -min_accelerator_micros 0 -min_cpu_micros 0 -min_params 0 -min_float_ops 1 -min_occurrence 0 -step -1 -order_by float_ops -account_type_regexes . -start_name_regexes . -trim_name_regexes
-show_name_regexes .* -hide_name_regexes
-account_displayed_op_only true -select float_ops -output stdout:

==================Model Analysis Report====================== Incomplete shape.

FanYans commented 5 months ago

me too