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License: MIT License
Hello, I would like to ask, if there is no instance in the picture, that is to say, the preprocessing detection network thinks that the picture has no object, then this picture cannot be colored?
Using the unmodified Google Colab Demo.
I think it has something to do with the zip file not being downloaded correctly. The size of the zip is only around 3KB. Maybe the Google Drive download is being rate limited?
Error:
initialize network with normal
initialize network with normal
initialize network with normal
model [FusionModel] was created
load Fusion model from checkpoints/coco_finetuned_mask_256_ffs/latest_net_GF.pth
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-11-e948e7e9ae19> in <module>()
1 model = create_model(opt)
----> 2 model.setup_to_test('coco_finetuned_mask_256_ffs')
3 frames
/content/InstColorization/models/fusion_model.py in setup_to_test(self, fusion_weight_path)
95 GF_path = 'checkpoints/{0}/latest_net_GF.pth'.format(fusion_weight_path)
96 print('load Fusion model from %s' % GF_path)
---> 97 GF_state_dict = torch.load(GF_path)
98
99 # G_path = 'checkpoints/coco_finetuned_mask_256/latest_net_G.pth' # fine tuned on cocostuff
/usr/local/lib/python3.6/dist-packages/torch/serialization.py in load(f, map_location, pickle_module, **pickle_load_args)
582 pickle_load_args['encoding'] = 'utf-8'
583
--> 584 with _open_file_like(f, 'rb') as opened_file:
585 if _is_zipfile(opened_file):
586 with _open_zipfile_reader(f) as opened_zipfile:
/usr/local/lib/python3.6/dist-packages/torch/serialization.py in _open_file_like(name_or_buffer, mode)
232 def _open_file_like(name_or_buffer, mode):
233 if _is_path(name_or_buffer):
--> 234 return _open_file(name_or_buffer, mode)
235 else:
236 if 'w' in mode:
/usr/local/lib/python3.6/dist-packages/torch/serialization.py in __init__(self, name, mode)
213 class _open_file(_opener):
214 def __init__(self, name, mode):
--> 215 super(_open_file, self).__init__(open(name, mode))
216
217 def __exit__(self, *args):
FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/coco_finetuned_mask_256_ffs/latest_net_GF.pth'
Hi, I have a question about my error.
I just run the train.py for fusion and had a error like this.
" stack expects each tensor to be equal size, but got [2, 3, 256, 256] at entry 0 and [8, 3, 256, 256] at entry 1 "
How can I fix it?
Hello, after reading you paper ,I want to run the code.But,I meet some questions.
1.I dont kown the checkpoints location. The struction is checkpoints/checkpoints /coco_fine......,or checkpoints/coco_fine....
2.The cocostuff dataset location is train_data/cocostuff/train2017.zip?
srroy,my code ability not good,so have these simple questions.
Chinese follow:
您好!我不太清楚这个预训练模型具体的摆放位置,是checkpoints文件夹下直接就是预训练的3个模型的文件夹,还是checkpoints->checkpoints->三个预训练模型文件夹。
还有就是这个cocostuff数据集的位置是,train_data/cocostuff,还是train_data/train.
请您指教
The colab env doesn't support requirement packages so installation cell fails:
Looking in links: https://download.pytorch.org/whl/cu101/torch_stable.html
ERROR: Could not find a version that satisfies the requirement torch==1.5 (from versions: 1.11.0, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.1.2)
ERROR: No matching distribution found for torch==1.5
Requirement already satisfied: cython in /usr/local/lib/python3.10/dist-packages (3.0.8)
Collecting pyyaml==5.1
Using cached PyYAML-5.1.tar.gz (274 kB)
error: subprocess-exited-with-error
× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
Preparing metadata (setup.py) ... error
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
Collecting git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI
Cloning https://github.com/cocodataset/cocoapi.git to /tmp/pip-req-build-688i0rmv
Running command git clone --filter=blob:none --quiet https://github.com/cocodataset/cocoapi.git /tmp/pip-req-build-688i0rmv
Resolved https://github.com/cocodataset/cocoapi.git to commit 8c9bcc3cf640524c4c20a9c40e89cb6a2f2fa0e9
Preparing metadata (setup.py) ... done
Requirement already satisfied: setuptools>=18.0 in /usr/local/lib/python3.10/dist-packages (from pycocotools==2.0) (67.7.2)
Requirement already satisfied: cython>=0.27.3 in /usr/local/lib/python3.10/dist-packages (from pycocotools==2.0) (3.0.8)
Requirement already satisfied: matplotlib>=2.1.0 in /usr/local/lib/python3.10/dist-packages (from pycocotools==2.0) (3.7.1)
Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (1.2.0)
Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (0.12.1)
Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (4.47.2)
Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (1.4.5)
Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (1.23.5)
Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (23.2)
Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (9.4.0)
Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (3.1.1)
Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=2.1.0->pycocotools==2.0) (2.8.2)
Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=2.1.0->pycocotools==2.0) (1.16.0)
Requirement already satisfied: dominate==2.4.0 in /usr/local/lib/python3.10/dist-packages (2.4.0)
Looking in links: https://dl.fbaipublicfiles.com/detectron2/wheels/cu101/index.html
ERROR: Could not find a version that satisfies the requirement detectron2==0.1.2 (from versions: none)
ERROR: No matching distribution found for detectron2==0.1.2
In networks, WeightGenerator. Why *100000.0?
你好,我用开源的代码跑了论文中的图,发现结果和论文展示的结果对不上,请问是否是哪里设置有问题呢?
First of all, great job on the project! I was wondering if there were any implemented functionality to finetune this model? Basically introducing another dataset to train on top of the already trained model.
Thanks in advance.
Hi @ericsujw,
Thanks for sharing this great work! I read through your paper but didn't find the model size and FLOPs. Could you share those here?
Excuse me, could you please release the model weights which are not fine-tuned on COCO-Stuff training set?
FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/coco_finetuned_mask_256_ffs/latest_net_GF.pth'
I got this in google collab. Any idea?
Hey @jbhuang0604,
Good job and thanks for sharing your code! I have a question about color space. Why do you select CIE Lab color space in order to predict the missing color channels (what are the intention behind this decision or what are the advantages of CIE Lab color space compare to other color spaces)?
Thanks!
Hi,
I'm experiencing strange color bleeds in many colorized images. See example urls below. Any advice on how to avoid this undesired effect?
https://i.imgur.com/MCg2ZaN.png
https://i.imgur.com/3qJniGV.png
https://i.imgur.com/k7QPUQA.png
Thanks in advance
Hello, could you realse more details about how to calculate the PSNR and SSIM? I tested the RGB results on your website which are resized to 256 in size with PSNR and SSIM function in skimage, but found all results of the existing works lower than listed in the paper.
Hi, thanks for sharing your code.
I followed your test step and try to test on the ImageNet test set. And I found the result is different from what you released on the website https://ericsujw.github.io/InstColorization/
Could you provide detailed steps on how to use your pretrained model to obtain the test result on ImageNet? Do you use the same setting to test on ImageNet as the setting on COCO-Stuff?
Hello.
I have a question about the color conversion and normalization.
Can you tell me what is the range of lab values after the conversion and why did you normalize 'L' value by subtracting 50 and divided by 100?
Also, why did you normalize 'ab' values by dividing them to 110?
Thank you in advance.
What is the structure of your backbone? It doesn’t seem to use gan or pix2pix.
Excuse me, could you please release the model weights which are not fine-tuned on COCO-Stuff training set?
It's a great job. Thank you !
Here ,I have two questions to ask your advice:
(1)My input image size is different such as 419* 320 , 520* 400.... ,but I found the size of result image all are 512*512,Is there any way to make the result image size consistent with the input image size?
(2) I have changed the Parameter:fineSize=512
for examle:
python test_fusion.py --name test_fusion --sample_p 1.0 --model fusion --fineSize 512 --test_img_dir example --results_img_dir results
,but Program error display:
"RuntimeError: CUDA out of memory. Tried to allocate 64.00 MiB (GPU 0; 10.91 GiB total capacity; 9.73 GiB already allocated; 56.38 MiB free; 9.83 GiB reserved in total by PyTorch)"
My GPU is 1080Ti.
The current output image size seems to be too small,How do I fix this problem?
in windows how to import it.when i use this poject in windows,whre should i change
When I want to train my own dataset, I found that, only stage=full can run well, stage=instance or fusion will get any exception for that, get an empty tensor.
So, now I can get the last_net_G.pth well, BUT I can't get last_net_GF & last_net_Gcomp.
Thanks.
From the results, it seems that the "coco_finetuned_mask_256_ffs" is trained without ground-truth hints provided, while the "coco_finetuned_mask_256" is trained with ground-truth hints used. But the strange thing is that the results shown in the paper are more likely to the latter.
Is that true?
First of all – thanks very much for making your code available. Impressive work! Very appreciated.
I tried to render higher resolutions than the default 256 x 256px and changed the argparse variables like so:
opt.fineSize = 512
opt.loadSize = 512
However, the Colab Pro notebook yields this error:
RuntimeError: CUDA out of memory. Tried to allocate 1.12 GiB (GPU 0; 15.90 GiB total capacity; 14.61 GiB already allocated; 502.94 MiB free; 14.70 GiB reserved in total by PyTorch)
How can I fix this or render higher resolutions in another way?
Thanks in advance!
Hi,
Thanks for the code! I am getting this issue whilst trying to install the dependencies when using this line conda env create --file env.yml
is there any solution to this. I have tried adding them to pip section.
Thanks in advance
`Solving environment: failed
ResolvePackageNotFound:
Using unmodified Googlecolab I got this error:
model = create_model(opt)
model.setup_to_test('coco_finetuned_mask_256_ffs')
FileNotFoundError Traceback (most recent call last)
in ()
1 model = create_model(opt)
----> 2 model.setup_to_test('coco_finetuned_mask_256_ffs')
3 frames
/usr/local/lib/python3.6/dist-packages/torch/serialization.py in init(self, name, mode)
213 class _open_file(_opener):
214 def init(self, name, mode):
--> 215 super(_open_file, self).init(open(name, mode))
216
217 def exit(self, *args):
FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/coco_finetuned_mask_256_ffs/latest_net_GF.pth'
Is there any way to run the script on a machine that doesn't have GPUs?
hi.I am confused of the meaning of box_info_2x/ box_info_4x/ box_info_8x in fusion_dataset.py.Any help would be greatly appreciated
Hi, I know this by some technology blog, and this is the best colorization project I have seen
I tried to run it on my personal ubuntu laptop, but I got this problem, I also tried use the docker environment(https://hub.docker.com/r/continuumio/anaconda3) to execute conda env create --file env.yml --name instacolorization
and got this error as same, can you support me some information about this?
['/opt/conda/envs/instacolorization/bin/python', '-m', 'pip', 'install', '-U', '-r', '/opt/InstColorization/condaenv.y2bkp0vm.requirements.txt']
Pip subprocess output:
Collecting absl-py==0.9.0
Downloading absl-py-0.9.0.tar.gz (104 kB)
Collecting cachetools==4.1.0
Downloading cachetools-4.1.0-py3-none-any.whl (10 kB)
Collecting chardet==3.0.4
Downloading chardet-3.0.4-py2.py3-none-any.whl (133 kB)Pip subprocess error:
ERROR: Could not find a version that satisfies the requirement detectron2==0.1.2+cu101 (from -r /opt/InstColorization/condaenv.y2bkp0vm.requirements.txt (line 4)) (from versions: none)
ERROR: No matching distribution found for detectron2==0.1.2+cu101 (from -r /opt/InstColorization/condaenv.y2bkp0vm.requirements.txt (line 4))CondaEnvException: Pip failed
Thanks.
Hi, great work!
Any chance to use your approach with videos? I've tried a little bit and now it's flickering a lot.
Hi,
Thanks for the great work! I am reproducing your work following README_TRAIN.md step by step, but encountered an error while running the Instance Prediction step:
sh scripts/prepare_train_box.sh
The error I got was:
Traceback (most recent call last):
File "inference_bbox.py", line 51, in <module>
outputs = predictor(l_stack)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/engine/defaults.py", line 218, in __call__
predictions = self.model([inputs])[0]
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
result = self.forward(*input, **kwargs)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 108, in forward
return self.inference(batched_inputs)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 161, in inference
features = self.backbone(images.tensor)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
result = self.forward(*input, **kwargs)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/modeling/backbone/fpn.py", line 123, in forward
bottom_up_features = self.bottom_up(x)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
result = self.forward(*input, **kwargs)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/modeling/backbone/resnet.py", line 454, in forward
x = self.stem(x)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
result = self.forward(*input, **kwargs)
File "/home/ztu/miniconda3/envs/instacolorization/lib/python3.7/site-packages/detectron2/modeling/backbone/resnet.py", line 391, in forward
x = F.relu_(x)
RuntimeError: CUDA error: no kernel image is available for execution on the device
Do you know how to fix this problem? Thanks!
I use the code:
python test_fusion.py --name test_fusion --sample_p 1.0 --model fusion --fineSize 256 --test_img_dir example --results_img_dir results
But I get results which are very blurred, I can't get the high-resolution vegetable image as in your colab. I can only get the blurred and square shape vegetable image. How can I solve it? Thank you!
Hi!
I would like to know, how to use the code to train with my own dataset?
Is there a code to run the training step in the repository?
Best regards,
Matheus Santos.
Hi !
I launched a training session on your model and I have few questions if I may:
latest_net_G.pth
(I get an error FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/coco_mask/latest_net_GF.pth'
if I don't copy your models weight when running FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/coco_mask/latest_net_GF.pth'
)Firstly, thanks for your code sharing. I use your partly code to convert image from RGB to Lab colorspace. I didn't change your code, but I encountered an error.
File "/content/drive/My Drive/BICYCLEGAN/dataset.py", line 36, in __getitem__
img_lab = rgb2lab(img)
File "/content/drive/My Drive/BICYCLEGAN/colorspace.py", line 126, in rgb2lab
lab = xyz2lab(rgb2xyz(rgb))
File "/content/drive/My Drive/BICYCLEGAN/colorspace.py", line 45, in rgb2xyz
x = .412453 * rgb[:, 0, :, :] + .357580 * rgb[:, 1, :, :] + .180423 * rgb[:, 2, :, :]
**IndexError: too many indices for tensor of dimension 3**
Could you give me some advice to solve this problem? Thanks.
Great work! And thanks for sharing the code.
I tried to combine another colorization method to this segmentation-colorization-fusion framework on a ubuntu computer with a GTX1080Ti GPU, but I'm confused that I did not find the file for training these models in your repo.
Could you share how you trained the models?
I follow this to train: https://github.com/ericsujw/InstColorization/blob/master/README_TRAIN.md
When I run
python test_fusion.py --name test_fusion --sample_p 1.0 --model fusion --fineSize 256 --test_img_dir example --results_img_dir results
I meet so many error:
#Testing images = 376
initialize network with normal
initialize network with normal
initialize network with normal
model [FusionModel] was created
load Fusion model from checkpoints/coco_mask/latest_net_GF.pth
0%| | 0/376 [00:00<?, ?it/s]Traceback (most recent call last):
File "", line 1, in
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 114, in _main
prepare(preparation_data)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 225, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 277, in _fixup_main_from_path
run_name="mp_main")
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/data/likengpeng/InstColorization/test_fusion.py", line 71, in
lab_image = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
cv2.error: OpenCV(4.2.0) /io/opencv/modules/imgproc/src/color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cvtColor'
Traceback (most recent call last):
File "", line 1, in
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 114, in _main
prepare(preparation_data)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 225, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/spawn.py", line 277, in _fixup_main_from_path
run_name="mp_main")
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/data/likengpeng/InstColorization/test_fusion.py", line 71, in
lab_image = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
cv2.error: OpenCV(4.2.0) /io/opencv/modules/imgproc/src/color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cvtColor'
Traceback (most recent call last):
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 761, in _try_get_data
data = self._data_queue.get(timeout=timeout)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/queues.py", line 104, in get
if not self._poll(timeout):
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/connection.py", line 257, in poll
return self._poll(timeout)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/connection.py", line 414, in _poll
r = wait([self], timeout)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/multiprocessing/connection.py", line 920, in wait
ready = selector.select(timeout)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/selectors.py", line 415, in select
fd_event_list = self._selector.poll(timeout)
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler
_error_if_any_worker_fails()
RuntimeError: DataLoader worker (pid 55739) exited unexpectedly with exit code 1. Details are lost due to multiprocessing. Rerunning with num_workers=0 may give better error trace.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "test_fusion.py", line 41, in
for data_raw in tqdm(dataset_loader, dynamic_ncols=True):
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/tqdm/std.py", line 1108, in iter
for obj in iterable:
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 841, in _next_data
idx, data = self._get_data()
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 808, in _get_data
success, data = self._try_get_data()
File "/home/amax/anaconda3/envs/instacolorization/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 774, in _try_get_data
raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
RuntimeError: DataLoader worker (pid(s) 55739) exited unexpectedly
0%| | 0/376 [00:02<?, ?it/s]
How can I solve them? Help me please!
Hello, I've read your paper recently. In this paper, you mentioned that the training epoch is set as 2, 5 and 2, but the source code is set 150. I want to know which is correct? Thank you!
Pretrained Model
InstColorization.ipynb 👍
!sh scripts/download_model.sh
or
!gdown https://drive.google.com/u/0/uc?id=1Xb-DKAA9ibCVLqm8teKd1MWk6imjwTBh&export=download
!unzip checkpoints.zip
🎨🔥😀👏
When I train, I code visdom -port 8098 and I can not enter into http://localhost:8098 to see loss. How can I solve it?
Hi there,
I am working on re-implementing your paper in TensorFlow. The details you provided regarding Instance and full image networks are straight-forward. But I request you to please provide more instructions on how exactly to fuse these to get results. Especially I am confused about how to utilize the bounding box co-ordinates of each instance and marking the location inside the full image and training on it.
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