Add support for i18n

demo_gradio.py

@@ -5,6 +5,8 @@
 os.environ['HF_HOME'] = os.path.abspath(os.path.realpath(os.path.join(os.path.dirname(__file__), './hf_download')))
 
 import gradio as gr
+from gradio_i18n import Translate
+from gradio_i18n import gettext as _
 import torch
 import traceback
 import einops
@@ -356,49 +358,52 @@ def end_process():
 
 css = make_progress_bar_css()
 block = gr.Blocks(css=css).queue()
+
+lang_list = ["en", "ja", "ko", "fr", "de", "es", "it", "pt", "ru", "tr", "pl", "ar", "zh-Hans", "zh-Hant"]
 with block:
-    gr.Markdown('# FramePack')
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(sources='upload', type="numpy", label="Image", height=320)
-            prompt = gr.Textbox(label="Prompt", value='')
-            example_quick_prompts = gr.Dataset(samples=quick_prompts, label='Quick List', samples_per_page=1000, components=[prompt])
-            example_quick_prompts.click(lambda x: x[0], inputs=[example_quick_prompts], outputs=prompt, show_progress=False, queue=False)
+    with Translate("translations.json", placeholder_langs=lang_list):
+        gr.Markdown('# FramePack')
+        with gr.Row():
+            with gr.Column():
+                input_image = gr.Image(sources='upload', type="numpy", label=_("Image"), height=320)
+                prompt = gr.Textbox(label=_("Prompt"), value='')
+                example_quick_prompts = gr.Dataset(samples=quick_prompts, label=_('Quick List'), samples_per_page=1000, components=[prompt])
+                example_quick_prompts.click(lambda x: x[0], inputs=[example_quick_prompts], outputs=prompt, show_progress=False, queue=False)
 
-            with gr.Row():
-                start_button = gr.Button(value="Start Generation")
-                end_button = gr.Button(value="End Generation", interactive=False)
+                with gr.Row():
+                    start_button = gr.Button(value=_("Start Generation"))
+                    end_button = gr.Button(value=_("End Generation"), interactive=False)
 
-            with gr.Group():
-                use_teacache = gr.Checkbox(label='Use TeaCache', value=True, info='Faster speed, but often makes hands and fingers slightly worse.')
+                with gr.Group():
+                    use_teacache = gr.Checkbox(label=_('Use TeaCache'), value=True, info=_('Faster speed, but often makes hands and fingers slightly worse.'))
 
-                n_prompt = gr.Textbox(label="Negative Prompt", value="", visible=False)  # Not used
-                seed = gr.Number(label="Seed", value=31337, precision=0)
+                    n_prompt = gr.Textbox(label=_("Negative Prompt"), value="", visible=False)  # Not used
+                    seed = gr.Number(label=_("Seed"), value=31337, precision=0)
 
-                total_second_length = gr.Slider(label="Total Video Length (Seconds)", minimum=1, maximum=120, value=5, step=0.1)
-                latent_window_size = gr.Slider(label="Latent Window Size", minimum=1, maximum=33, value=9, step=1, visible=False)  # Should not change
-                steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=25, step=1, info='Changing this value is not recommended.')
+                    total_second_length = gr.Slider(label=_("Total Video Length (Seconds)"), minimum=1, maximum=120, value=5, step=0.1)
+                    latent_window_size = gr.Slider(label=_("Latent Window Size"), minimum=1, maximum=33, value=9, step=1, visible=False)  # Should not change
+                    steps = gr.Slider(label=_("Steps"), minimum=1, maximum=100, value=25, step=1, info=_('Changing this value is not recommended.'))
 
-                cfg = gr.Slider(label="CFG Scale", minimum=1.0, maximum=32.0, value=1.0, step=0.01, visible=False)  # Should not change
-                gs = gr.Slider(label="Distilled CFG Scale", minimum=1.0, maximum=32.0, value=10.0, step=0.01, info='Changing this value is not recommended.')
-                rs = gr.Slider(label="CFG Re-Scale", minimum=0.0, maximum=1.0, value=0.0, step=0.01, visible=False)  # Should not change
+                    cfg = gr.Slider(label=_("CFG Scale"), minimum=1.0, maximum=32.0, value=1.0, step=0.01, visible=False)  # Should not change
+                    gs = gr.Slider(label=_("Distilled CFG Scale"), minimum=1.0, maximum=32.0, value=10.0, step=0.01, info=_('Changing this value is not recommended.'))
+                    rs = gr.Slider(label=_("CFG Re-Scale"), minimum=0.0, maximum=1.0, value=0.0, step=0.01, visible=False)  # Should not change
 
-                gpu_memory_preservation = gr.Slider(label="GPU Inference Preserved Memory (GB) (larger means slower)", minimum=6, maximum=128, value=6, step=0.1, info="Set this number to a larger value if you encounter OOM. Larger value causes slower speed.")
+                    gpu_memory_preservation = gr.Slider(label=_("GPU Inference Preserved Memory (GB) (larger means slower)"), minimum=6, maximum=128, value=6, step=0.1, info=_("Set this number to a larger value if you encounter OOM. Larger value causes slower speed."))
 
-                mp4_crf = gr.Slider(label="MP4 Compression", minimum=0, maximum=100, value=16, step=1, info="Lower means better quality. 0 is uncompressed. Change to 16 if you get black outputs. ")
+                    mp4_crf = gr.Slider(label=_("MP4 Compression"), minimum=0, maximum=100, value=16, step=1, info=_("Lower means better quality. 0 is uncompressed. Change to 16 if you get black outputs. "))
 
-        with gr.Column():
-            preview_image = gr.Image(label="Next Latents", height=200, visible=False)
-            result_video = gr.Video(label="Finished Frames", autoplay=True, show_share_button=False, height=512, loop=True)
-            gr.Markdown('Note that the ending actions will be generated before the starting actions due to the inverted sampling. If the starting action is not in the video, you just need to wait, and it will be generated later.')
-            progress_desc = gr.Markdown('', elem_classes='no-generating-animation')
-            progress_bar = gr.HTML('', elem_classes='no-generating-animation')
+            with gr.Column():
+                preview_image = gr.Image(label=_("Next Latents"), height=200, visible=False)
+                result_video = gr.Video(label=_("Finished Frames"), autoplay=True, show_share_button=False, height=512, loop=True)
+                gr.Markdown(_('Note that the ending actions will be generated before the starting actions due to the inverted sampling. If the starting action is not in the video, you just need to wait, and it will be generated later.'))
+                progress_desc = gr.Markdown('', elem_classes='no-generating-animation')
+                progress_bar = gr.HTML('', elem_classes='no-generating-animation')
 
-    gr.HTML('<div style="text-align:center; margin-top:20px;">Share your results and find ideas at the <a href="https://x.com/search?q=framepack&f=live" target="_blank">FramePack Twitter (X) thread</a></div>')
+        gr.HTML('<div style="text-align:center; margin-top:20px;">Share your results and find ideas at the <a href="https://x.com/search?q=framepack&f=live" target="_blank">FramePack Twitter (X) thread</a></div>')
 
-    ips = [input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf]
-    start_button.click(fn=process, inputs=ips, outputs=[result_video, preview_image, progress_desc, progress_bar, start_button, end_button])
-    end_button.click(fn=end_process)
+        ips = [input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf]
+        start_button.click(fn=process, inputs=ips, outputs=[result_video, preview_image, progress_desc, progress_bar, start_button, end_button])
+        end_button.click(fn=end_process)
 
 
 block.launch(

requirements.txt

@@ -13,3 +13,4 @@ torchsde==0.2.6
 einops
 opencv-contrib-python
 safetensors
+gradio-i18n