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Update app.py
Browse files
app.py
CHANGED
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@@ -80,7 +80,7 @@ def create_error_image(message):
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def classify_prompt(prompt):
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inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
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outputs = model(**inputs)
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return torch.argmax(outputs.logits).item()
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@@ -96,6 +96,21 @@ def image_to_base64(file_path):
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except Exception as e:
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raise ValueError(f"Base64编码失败: {str(e)}")
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def generate_video(
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context_scale,
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enable_safety_checker,
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@@ -128,21 +143,18 @@ def generate_video(
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session['last_active'] = time.time()
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session['count'] += 1
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API_KEY =
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if not API_KEY:
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error_img = create_error_image("API key not found")
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yield "❌ Error: Missing API Key", error_img
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return
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try:
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if not images or len(images) < 2:
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raise ValueError("must provide at least 2 images")
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base64_images = []
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except Exception as e:
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error_img = create_error_image(str(e))
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yield f"❌failed to upload images: {str(e)}", error_img
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@@ -155,6 +167,15 @@ def generate_video(
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else:
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video_payload = video
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payload = {
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"context_scale": context_scale,
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"enable_fast_mode": enable_fast_mode,
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@@ -283,23 +304,23 @@ with gr.Blocks(
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random_seed_btn = gr.Button("Random🎲Seed", variant="secondary", elem_id="centered_button")
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with gr.Row():
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enable_safety_checker = gr.Checkbox(True, label="Enable Safety Checker", interactive=True)
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enable_fast_mode = gr.Checkbox(
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with gr.Column(scale=1):
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video_output = gr.Video(label="Video Output", format="mp4", interactive=False, elem_classes=["video-preview"])
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generate_btn = gr.Button("Generate", variant="primary")
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status_output = gr.Textbox(label="status", interactive=False, lines=4)
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gr.Examples(
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[
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"https://d2g64w682n9w0w.cloudfront.net/media/ec44bbf6abac4c25998dd2c4af1a46a7/images/1747413751234102420_md9ywspl.png",
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"https://d2g64w682n9w0w.cloudfront.net/media/ec44bbf6abac4c25998dd2c4af1a46a7/images/1747413586520964413_7bkgc9ol.png"
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]
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]
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],
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random_seed_btn.click(
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fn=lambda: random.randint(0, 999999),
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@@ -344,5 +365,6 @@ if __name__ == "__main__":
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app.queue(max_size=4).launch(
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server_name="0.0.0.0",
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max_threads=16,
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share=False
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)
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def classify_prompt(prompt):
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inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
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with torch.no_grad():
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outputs = model(**inputs)
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return torch.argmax(outputs.logits).item()
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except Exception as e:
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raise ValueError(f"Base64编码失败: {str(e)}")
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def video_to_base64(file_path):
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"""
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将视频文件转换为Base64格式
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"""
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try:
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with open(file_path, "rb") as video_file:
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raw_data = video_file.read()
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encoded = base64.b64encode(raw_data)
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missing_padding = len(encoded) % 4
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if missing_padding:
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encoded += b'=' * (4 - missing_padding)
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return encoded.decode('utf-8')
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except Exception as e:
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raise ValueError(f"Base64编码失败: {str(e)}")
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def generate_video(
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context_scale,
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enable_safety_checker,
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session['last_active'] = time.time()
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session['count'] += 1
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API_KEY = "30a09de38569400bcdab9cec1c9a660b1924a2b5f54aa386eeb87f96a112fb93"
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if not API_KEY:
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error_img = create_error_image("API key not found")
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yield "❌ Error: Missing API Key", error_img
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return
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try:
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base64_images = []
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if images is not None: # 检查 images 是否为 None
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for img_path in images:
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base64_img = image_to_base64(img_path)
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base64_images.append(base64_img)
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except Exception as e:
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error_img = create_error_image(str(e))
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yield f"❌failed to upload images: {str(e)}", error_img
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else:
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video_payload = video
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# 将视频文件转换为Base64格式
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try:
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base64_video = video_to_base64(video_payload)
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video_payload = base64_video
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except Exception as e:
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error_img = create_error_image(str(e))
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yield f"❌ Failed to encode video: {str(e)}", error_img
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return
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payload = {
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"context_scale": context_scale,
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"enable_fast_mode": enable_fast_mode,
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random_seed_btn = gr.Button("Random🎲Seed", variant="secondary", elem_id="centered_button")
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with gr.Row():
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enable_safety_checker = gr.Checkbox(True, label="Enable Safety Checker", interactive=True)
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enable_fast_mode = gr.Checkbox(True, label="To enable the fast mode, please visit Wave Speed AI", interactive=False)
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with gr.Column(scale=1):
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video_output = gr.Video(label="Video Output", format="mp4", interactive=False, elem_classes=["video-preview"])
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generate_btn = gr.Button("Generate", variant="primary")
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status_output = gr.Textbox(label="status", interactive=False, lines=4)
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gr.Examples(
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examples=[
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[
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"The elegant lady carefully selects bags in the boutique, and she shows the charm of a mature woman in a black slim dress with a pearl necklace, as well as her pretty face. Holding a vintage-inspired blue leather half-moon handbag, she is carefully observing its craftsmanship and texture. The interior of the store is a haven of sophistication and luxury. Soft, ambient lighting casts a warm glow over the polished wooden floors",
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[
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"https://d2g64w682n9w0w.cloudfront.net/media/ec44bbf6abac4c25998dd2c4af1a46a7/images/1747413751234102420_md9ywspl.png",
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"https://d2g64w682n9w0w.cloudfront.net/media/ec44bbf6abac4c25998dd2c4af1a46a7/images/1747413586520964413_7bkgc9ol.png"
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]
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]
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],
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inputs=[prompt, images],
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)
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random_seed_btn.click(
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fn=lambda: random.randint(0, 999999),
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app.queue(max_size=4).launch(
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server_name="0.0.0.0",
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max_threads=16,
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server_port=8009,
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share=False
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)
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