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Browse files- stCompressService.py +16 -16
stCompressService.py
CHANGED
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@@ -89,7 +89,7 @@ def main(debug: bool, quiet: bool, qp: int, disable_gpu: bool):
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</p>
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<
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> Due to resources limitation, I only provide compression service with model `qp = 3`.
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@@ -102,22 +102,22 @@ def main(debug: bool, quiet: bool, qp: int, disable_gpu: bool):
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<br/>
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<a href="https://github.com/xiaosu-zhu/McQuic">
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<
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<
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</a>
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""", unsafe_allow_html=True)
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if HF_SPACE:
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st.markdown("""
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<
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> Due to resources limitation of HF spaces, the upload image size is restricted to lower than `3000 x 3000`.
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<
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> Also, this demo running on HF space is GPU-disabled. So it may be slow.
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""")
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with st.form("SubmitForm"):
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uploadedFile = st.file_uploader("Try running McQuic to compress or restore images!", type=["png", "jpg", "jpeg", "mcq"], help="Upload your image or compressed `.mcq` file here.")
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cropping = st.checkbox("Cropping image to align grids.", help="If checked, the image is cropped to align feature map grids. This will make compressed file smaller.")
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@@ -138,18 +138,18 @@ def main(debug: bool, quiet: bool, qp: int, disable_gpu: bool):
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a = Image.open(uploadedFile)
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except PIL.UnidentifiedImageError:
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st.markdown("""
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<
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> Image open failed. Please try other images.
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""")
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return
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w, h = a.size
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if HF_SPACE and (h > 3000 or w > 3000):
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st.markdown("""
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<
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> Image is too large. Please try other images.
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""")
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return
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raw = torch.ByteTensor(torch.ByteStorage.from_buffer(uploadedFile.read())) # type: ignore
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image = decode_image(raw, ImageReadMode.RGB).to(device)
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@@ -170,19 +170,19 @@ def main(debug: bool, quiet: bool, qp: int, disable_gpu: bool):
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<p align="center">
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<a href="https://www.python.org/" target="_blank">
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<
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</a>
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<a href="https://pytorch.org/" target="_blank">
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<
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/stargazers" target="_blank">
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<
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/network/members" target="_blank">
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<
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/blob/main/LICENSE" target="_blank">
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<
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</a>
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</p>
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@@ -192,7 +192,7 @@ def main(debug: bool, quiet: bool, qp: int, disable_gpu: bool):
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<p align="center"><a href="localhost" target="_blank">CVF Open Access</a> | <a href="localhost" target="_blank">arXiv</a> | <a href="https://github.com/xiaosu-zhu/McQuic#citation" target="_blank">BibTex</a> | <a href="https://huggingface.co/spaces/xiaosu-zhu/McQuic">Demo</a></p>
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""")
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if __name__ == "__main__":
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with torch.inference_mode():
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</p>
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<img src="https://img.shields.io/badge/NOTE-yellow?style=for-the-badge" alt="NOTE"/>
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> Due to resources limitation, I only provide compression service with model `qp = 3`.
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<br/>
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<a href="https://github.com/xiaosu-zhu/McQuic">
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<img src="https://raw.githubusercontent.com/xiaosu-zhu/McQuic/main/assets/GitHub-Mark-120px-plus.png" alt="Github"/>
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<img src="https://img.shields.io/github/stars/xiaosu-zhu/McQuic?style=social" alt="Github"/>
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</a>
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""", unsafe_allow_html=True)
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if HF_SPACE:
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st.markdown("""
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<img src="https://img.shields.io/badge/NOTE-yellow?style=for-the-badge" alt="NOTE"/>
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> Due to resources limitation of HF spaces, the upload image size is restricted to lower than `3000 x 3000`.
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<img src="https://img.shields.io/badge/NOTE-yellow?style=for-the-badge" alt="NOTE"/>
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> Also, this demo running on HF space is GPU-disabled. So it may be slow.
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""", unsafe_allow_html=True)
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with st.form("SubmitForm"):
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uploadedFile = st.file_uploader("Try running McQuic to compress or restore images!", type=["png", "jpg", "jpeg", "mcq"], help="Upload your image or compressed `.mcq` file here.")
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cropping = st.checkbox("Cropping image to align grids.", help="If checked, the image is cropped to align feature map grids. This will make compressed file smaller.")
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a = Image.open(uploadedFile)
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except PIL.UnidentifiedImageError:
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st.markdown("""
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<img src="https://img.shields.io/badge/ERROR-red?style=for-the-badge" alt="ERROR"/>
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> Image open failed. Please try other images.
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""", unsafe_allow_html=True)
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return
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w, h = a.size
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if HF_SPACE and (h > 3000 or w > 3000):
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st.markdown("""
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<img src="https://img.shields.io/badge/ERROR-red?style=for-the-badge" alt="ERROR"/>
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> Image is too large. Please try other images.
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""", unsafe_allow_html=True)
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return
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raw = torch.ByteTensor(torch.ByteStorage.from_buffer(uploadedFile.read())) # type: ignore
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image = decode_image(raw, ImageReadMode.RGB).to(device)
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<p align="center">
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<a href="https://www.python.org/" target="_blank">
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<img src="https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54" alt="Python"/>
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</a>
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<a href="https://pytorch.org/" target="_blank">
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<img src="https://img.shields.io/badge/PyTorch-%23EE4C2C.svg?style=for-the-badge&logo=PyTorch&logoColor=white" alt="PyTorch"/>
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/stargazers" target="_blank">
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<img src="https://img.shields.io/github/stars/xiaosu-zhu/McQuic?logo=github&style=for-the-badge" alt="Github stars"/>
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/network/members" target="_blank">
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<img src="https://img.shields.io/github/forks/xiaosu-zhu/McQuic?logo=github&style=for-the-badge" alt="Github forks"/>
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</a>
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<a href="https://github.com/xiaosu-zhu/McQuic/blob/main/LICENSE" target="_blank">
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<img src="https://img.shields.io/github/license/xiaosu-zhu/McQuic?logo=github&style=for-the-badge" alt="Github license"/>
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</a>
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</p>
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<p align="center"><a href="localhost" target="_blank">CVF Open Access</a> | <a href="localhost" target="_blank">arXiv</a> | <a href="https://github.com/xiaosu-zhu/McQuic#citation" target="_blank">BibTex</a> | <a href="https://huggingface.co/spaces/xiaosu-zhu/McQuic">Demo</a></p>
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""", unsafe_allow_html=True)
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if __name__ == "__main__":
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with torch.inference_mode():
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