Create app.py

app.py

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+#@title Setup
+import os, subprocess
+
+def setup():
+    install_cmds = [
+        ['pip', 'install', 'ftfy', 'gradio', 'regex', 'tqdm', 'transformers==4.21.2', 'timm', 'fairscale', 'requests'],
+        ['pip', 'install', 'open_clip_torch'],
+        ['pip', 'install', '-e', 'git+https://github.com/pharmapsychotic/BLIP.git@lib#egg=blip'],
+        ['git', 'clone', '-b', 'open-clip', 'https://github.com/pharmapsychotic/clip-interrogator.git']
+    ]
+    for cmd in install_cmds:
+        print(subprocess.run(cmd, stdout=subprocess.PIPE).stdout.decode('utf-8'))
+
+setup()
+
+# download cache files
+print("Download preprocessed cache files...")
+CACHE_URLS = [
+    'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_artists.pkl',
+    'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_flavors.pkl',
+    'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_mediums.pkl',
+    'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_movements.pkl',
+    'https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_trendings.pkl',
+]
+os.makedirs('cache', exist_ok=True)
+for url in CACHE_URLS:
+    print(subprocess.run(['wget', url, '-P', 'cache'], stdout=subprocess.PIPE).stdout.decode('utf-8'))
+
+import sys
+sys.path.append('src/blip')
+sys.path.append('clip-interrogator')
+
+import gradio as gr
+from clip_interrogator import Config, Interrogator
+
+config = Config()
+config.blip_offload = True
+config.chunk_size = 2048
+config.flavor_intermediate_count = 512
+config.blip_num_beams = 64
+
+ci = Interrogator(config)
+
+def inference(image, mode, best_max_flavors):
+    image = image.convert('RGB')
+    if mode == 'best':
+        return ci.interrogate(image, max_flavors=int(best_max_flavors))
+    elif mode == 'classic':
+        return ci.interrogate_classic(image)
+    else:
+        return ci.interrogate_fast(image)
+
+inputs = [
+    gr.inputs.Image(type='pil'),
+    gr.Radio(['best', 'classic', 'fast'], label='', value='best'),
+    gr.Number(value=4, label='best mode max flavors'),
+]
+outputs = [
+    gr.outputs.Textbox(label="Output"),
+]
+
+io = gr.Interface(
+    inference, 
+    inputs, 
+    outputs, 
+    allow_flagging=False,
+)
+io.launch()